We’re committed to putting people first – if you need an accommodation as you go through the job searching, application, and interviewing process, please click here for more information.
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Develop technology enabled recommendations to address gaps within a single business process. Participate in the development of tools and methodologies and adapt them to the organization environment. Manage peer to peer relationships, with colleagues, vendors and external contractors, including offshore functions. Assist with development and execution of cutover plans for simple processes. Assist in post-implementation support, resolving issues and raising defects to appropriate level. Execute transition plan for area of responsibility to the appropriate resource for each phase of the project or initiative. Employer will accept a Bachelor's degree in Computer Science, Engineering [any] or related field and five (5) years of experience in the job offered or in a Solutions Engineer, Data-related occupation. * Design and implement data solutions of high complexity including data solutions for applications with a Mean Time To Recovery of 4 hours or less. Work closely with application team to ensure data needs meet business needs and align with architecture standards for support and security. Create applications with a high degree of observability utilizing Observability tools including Datadog. Guide senior level engineers on design practices and work closely with architects to influence strategic decisions. Drive the identification of key enablers and maintain a 12-month roadmap for aligned software products to meet business needs. Proficiency with Relational Databases and NoSQL databases including Oracle. Proficiency with cloud-based providers and containerized solutions including AWS. Experience may be gained during graduate program. Will accept any suitable combination of education, training, and/or experience. Multiple Positions Available.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618518641267", "isPrivate": false, "latlongs": "42.0629915,-88.12271989999999"}, {"id": 618518490234, "name": "Senior Data Engineer", "posting_name": "Senior Data Engineer", "location": "Boston, Massachusetts, United States", "locations": ["Boston, Massachusetts, United States", "Portsmouth, New Hampshire, United States", "Indianapolis, Indiana, United States"], "hot": 0, "department": "Technology", "business_unit": "0027-LM Technology-US", "t_update": 1784748240, "t_create": 1784226000, "ats_job_id": "76862", "display_job_id": "2026-76862", "type": "ATS", "id_locale": "2026-76862-en", "job_description": "Design, develop, and maintain scalable data pipelines, data models, and integration processes using modern cloud-based technologies (AWS, Snowflake, etc.) Analyze complex data sets and technical problems to design effective, flexible, and innovative solutions that meet business needs Collaborate closely with Product Owners, business stakeholders, and cross-functional teams to translate business requirements into technical data solutions Build and support ETL/ELT pipelines for structured and unstructured data from internal and external sources, including APIs, flat files, and enterprise applications Implement data quality checks, validation rules, reconciliations, exception handling, and monitoring to ensure data integrity Develop automated tests across multiple scopes (Unit, System, Integration, Regression) to ensure reliability and accuracy of data solutions Perform data profiling, root cause analysis, and troubleshooting of data issues across production and non-production environments Document data flows, data dictionaries, and technical specifications to support data governance and knowledge sharing Identify and recommend continuous improvement opportunities across data engineering processes and tooling Collaborate with engineers and architects, and actively contribute to code reviews and engineering best practices Leverage AI-assisted development tools like GitHub Copilot Bachelor's degree in computer science, Engineering, Information Systems, or a related technical or business discipline (or equivalent experience) 5-6 years of experience in data engineering, data analytics, or a related technical role Strong proficiency in SQL, including writing complex queries, data modeling, and working with relational and analytical databases Familiarity with cloud-based data platforms and tools such as Snowflake, AWS or similar technologies Strong analytical and problem-solving skills with the ability to interpret and communicate data-driven insights Demonstrated ability to work in an agile, squad-based environment with cross-functional teams Proactive, self-motivated, and a logical thinker with strong attention to detail Excellent written and verbal communication skills, with the ability to clearly convey technical concepts to non-technical stakeholders Experience with data integration and ETL/ELT tools such as IDMC Familiarity with CI/CD pipelines, version control (Git), and software development best practices Understanding of Cloud / Hybrid data architecture concepts Exposure to data governance, data quality frameworks, or master data management concepts Experience in the insurance or financial services industry is a plus Guidewire experience a plus.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618518490234", "isPrivate": false, "latlongs": "42.3555076,-71.0565364"}, {"id": 618514571625, "name": "Investments Data Product Owner - Liberty Mutual Investments", "posting_name": "Investments Data Product Owner - Liberty Mutual Investments", "location": "Boston, Massachusetts, United States", "locations": ["Boston, Massachusetts, United States", "New York, New York, United States"], "hot": 0, "department": "Investments", "business_unit": "3022-Liberty Mutual Investments (LMI)-US", "t_update": 1784139660, "t_create": 1765574760, "ats_job_id": "73623", "display_job_id": "2025-73623", "type": "ATS", "id_locale": "2025-73623-en", "job_description": "Own the vision, strategy, and roadmap for sourcing, integrating and curating external market data into LMI's data warehouse and core data products. Develop and manage the product backlog, ensuring clear prioritization aligned with business value, technical dependencies, and stakeholder needs across the investment data ecosystem. Partner closely with the Data Engineering chapter to design and deliver scalable, well-governed, and high-quality data solutions across key investment data domains (e.g., security and company reference data, pricing, positions, transactions, benchmarks, and analytics). Act as the voice of the customer\u2014portfolio managers, traders, investment analysts, operations, risk, and compliance\u2014to ensure investment data is accurately modeled, curated, and accessible to meet end-user needs and decision-making requirements. Champion the integration of data across the investment lifecycle, connecting front-office trading and portfolio management, middle-office risk and performance, and back-office accounting and operations. Drive incremental delivery using Agile methodologies, facilitating sprint planning, review, and refinement activities. Ensure that data products adhere to LMI's standards for data governance, lineage, accessibility, and quality, with a focus on the unique demands of investment data accuracy and timeliness. Bachelor's degree in Computer Science, Engineering, Finance, or Business Administration (advanced degree preferred). 8+ years of experience as a Product Owner, Data Product Manager, or Data Strategist within financial services, preferably investment or asset management. Demonstrable knowledge of investment data domains, including security reference data, company/issuer reference data, benchmarks and indices, pricing and valuations, positions, holdings, and transactions across multiple asset classes (equities, fixed income, derivatives, and alternatives a plus). Strong understanding of how investment data flows through the trade lifecycle and supports portfolio management, performance, risk, and regulatory reporting. Strong understanding of data management concepts\u2014master data management, metadata, data lineage, and data quality frameworks\u2014applied specifically to investment data. Hands-on exposure to order management systems (OMS), accounting book of record (ABOR/IBOR), and market data vendor platforms (e.g., Bloomberg, Refinitiv, ICE, MSCI). Experience working in Agile/Scrum environments with a strong ability to lead, prioritize, and manage multiple workstreams. Excellent communication and storytelling skills; able to translate complex investment data concepts into clear business terms for both technical and investment audiences. Strong analytical and critical-thinking skills with a focus on driving business value through data. Demonstrated proficiency in SQL and AI tools; experience with Snowflake a plus.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618514571625", "isPrivate": false, "latlongs": "42.3555076,-71.0565364"}, {"id": 618518607640, "name": "Senior Analyst, Advanced Analytics", "posting_name": "Senior Analyst, Advanced Analytics", "location": "Remote, Remote, United States", "locations": ["Remote, Remote, United States"], "hot": 0, "department": "Strategy & Planning", "business_unit": "3006-USRM-Finance-US", "t_update": 1785175260, "t_create": 1784741820, "ats_job_id": "76908", "display_job_id": "2026-76908", "type": "ATS", "id_locale": "2026-76908-en", "job_description": "Dedicate 80% of your time developing, coding, and testing fraud scenarios to generate efficacious leads for the Internal Sales and Service Fraud Investigation team by using advanced data analysis techniques and tools (e.g. Snowflake, SQL, SAS, PowerBI, etc.). Directly support our Internal Sales and Service Fraud Investigation stakeholders by leveraging marketing, distribution, and call data to identify suspicious patterns, anomalies, and emerging fraud trends across lines of business; including ad hoc requests to support active and future investigations. Partner with Fraud Hub leaders on strategic priorities and collaborate with Data Science and Reporting partners to integrate your insights into impactful dashboards and modeling solutions. Support the Analytics Asst Director to refine and update the framework that defines how we value potential Internal Sales and Service fraud leads. Develop operational health metrics and deliver data-driven narratives for the monthly operational review (MOR), surfacing performance drivers and improvement opportunities. Define best-in-class standards for fraud analytics excellence, institutionalize domain-specific business and technical expertise, and drive \u201cbuild-once-reuse-many\u201d framework. Experience with Internal Sales and Service data is a strong plus (or experience with financial fraud). Strong technical and analytical skills, experience working with large datasets and advanced coding techniques (preferably SQL). Strong stakeholder orientation: able to actively listen to and understand the stakeholder's needs; understand the stakeholder's end goal so you can deliver data and analyses that are usable and timely. Proven ability to successfully tackle high complexity analysis with minimal direction. You think critically and holistically about the data and analysis that will best serve our stakeholders. Manage and set expectations proactively and independently across multiple workstreams. Possess subject matter expertise in your domain and the ability to tell compelling stories with data. Champion continuous improvement by developing resources and institutionalizing knowledge. Bachelor's Degree plus a minimum 3 years, typically 4 or more years of experience, or equivalent, is required. Mathematics, Economics, Statistics or other quantitative field are preferred fields of study. Advanced knowledge of data sources, tools, statistical principles and methodologies, and techniques. Advanced proficiency in Excel (VBA, macros, scripts, formulas, data visualization, etc.), PowerPoint, and statistical software packages (SAS, Emblem). Must have good planning, analytical, decision-making and communication skills. Solid understanding of business to improve business outcomes.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "remote_local", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618518607640", "isPrivate": false, "latlongs": "37.09024,-95.712891"}, {"id": 618518427960, "name": "Wholesale Operations Leader - GRS North America", "posting_name": "Wholesale Operations Leader - GRS North America", "location": "Boston, Massachusetts, United States", "locations": ["Boston, Massachusetts, United States", "Remote, Remote, United States", "Plano, Texas, United States", "Hoffman Estates, Illinois, United States", "Indianapolis, Indiana, United States", "Lake Oswego, Oregon, United States", "Las Vegas, Nevada, United States", "Suwanee, Georgia, United States", "Weatogue, Connecticut, United States"], "hot": 0, "department": "Underwriting", "business_unit": "3026-GRS-North America-US", "t_update": 1784562780, "t_create": 1784035980, "ats_job_id": "76824", "display_job_id": "2026-76824", "type": "ATS", "id_locale": "2026-76824-en", "job_description": "Through a strategic and operational lens, lead cross-functional work to drive a collaborative, agile, high-performing culture and operating model that is principled, profitable, innovative, and nimble. Serve as a strategic thought partner to the Wholesale segment leader \u2014 contributing to the formation of segment strategy, not only its execution \u2014 including portfolio direction, distribution strategy, and growth priorities across E&S lines. Serve as Wholesale Operations Leader, representing Wholesale in Office of Underwriting, operations, product, data, and technology forums to ensure Ironshore's needs are built into roadmaps, not accommodated after the fact. Engineer the submission-to-quote pipeline as a measurable system with defined cycle time targets by business unit \u2014 identifying where time dies and building solutions to eliminate it. Own broker connectivity as a product decision, supporting API-first integration into broker AMS systems and reducing reliance on additional portals that create friction for brokers and underwriters. Make AI infrastructure foundational to the Wholesale operating model, enabling triage, clearance, and appetite scoring before a human touches a submission. Own submission-level data as the operating nervous system, including quote ratios, hit rates, cycle times by underwriter and by broker, and other key measures of underwriting and operational performance. Translate the six execution workstreams into a sequenced, resourced plan with clear owners, milestones, outcomes, and accountability. Build and own the standalone Wholesale P&L infrastructure in partnership with Finance, including the data architecture needed to make performance visible at the segment level. Partner with underwriting, actuarial, claims, finance, data, and technology teams to develop dashboards, portfolio analysis, operational reporting, and business insights to support segment and business unit leaders. Effectively prioritize and execute key operational initiatives across the Wholesale segment with strong project management discipline while championing Liberty Values & Guidelines to drive employee engagement, best-in-class service, productivity, and profitability. Accountable for ensuring clarity, visibility, and execution relative to operational key performance indicators KPIs across the Wholesale segment. Partner with segment and business unit leaders to organize and lead key operational meetings, manage competing priorities, and ensure decisions are translated into execution. Develop executive-level communications, business updates, decision materials, and reporting for internal and external stakeholders. Perform business analyses and evaluate the impact of alternative management decisions on operational outcomes, financial results, and broker/underwriter experience. May lead small team of operations resources supporting overall Wholesale priorities Deep expertise in Excess & Surplus (E&S) and wholesale/specialty insurance \u2014 spanning open-brokerage, SME binding authority, and delegated authority / program business \u2014 finance and actuarial concepts, regulatory environment, reinsurance, underwriting, producer management, and broker distribution. Advanced knowledge of financial analysis, technology, strategic planning, operational management, data/reporting, and business process improvement. Excellent oral and written communication skills, with strong presentation skills and the ability to facilitate discussion, influence stakeholders, and build consensus. Skills required include analyzing and problem solving; adaptability; decision making; building relationships; working effectively with others; applying financial acumen; focusing on service; executing excellence; planning and organizing work; and achieving results. Demonstrated ability to foster collaborative relationships and effectively work as part of a broader global and organizational team. Experience working in an Agile environment, e.g., agile project management, product ownership, workflow modernization, or technology-enabled operating model transformation. Excellent time management, prioritization, and delegation skills. Advanced degree or equivalent training preferred; CPCU designation or equivalent preferred. Experience managing and mentoring staff or leading cross-functional teams preferred. 12+ years of experience in operations, systems, organizational improvement, underwriting operations, strategy, business transformation, or related insurance roles.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "remote_local", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618518427960", "isPrivate": false, "latlongs": "42.3555076,-71.0565364"}, {"id": 618517331003, "name": "Principal Quantitative Engineer, Investments Technology", "posting_name": "Principal Quantitative Engineer, Investments Technology", "location": "Boston, Massachusetts, United States", "locations": ["Boston, Massachusetts, United States"], "hot": 0, "department": "Technology", "business_unit": "0027-LM Technology-US", "t_update": 1782241440, "t_create": 1779393180, "ats_job_id": "76155", "display_job_id": "2026-76155", "type": "ATS", "id_locale": "2026-76155-en", "job_description": "Lead the design and implementation of applications, proofs of concept, and production-grade tooling that advance portfolio construction, asset allocation analytics, and quantitative research workflows. Partner with quantitative analysts and portfolio strategists to convert AI-generated prototypes and research artifacts into robust, production-ready applications. Build and maintain data pipelines for portfolio and market data across public and private markets, leveraging the LMI data ecosystem. Contribute to the team's shared quantitative library, supporting both existing and new models, analytics, and reusable components. Support and extend existing applications and dashboards in production, and drive the design and implementation of new ones to meet evolving research and decision-support needs. Excellent problem-solving and analytical skills, with the ability to think critically, independently, and act with minimal handholding Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders. Strong attention to detail, organization, and the ability to manage multiple tasks and priorities in a fast-paced environment. Full-stack development knowledge with a minimum of 5 years professional experience programming in Python demonstrating the ability to write efficient and robust code able to process and analyze large financial datasets. Experience with key Python Libraries (pandas, NumPy) required Experience in front-end development and user experience (UX) design required; experience with Pythonic front-end and data visualization libraries (e.g., Plotly, Dash) preferred. Experience using Version Control (Git) required. Experience using Agentic Programming tools (Github Copilot, Claude) required. Experience developing applications for investment management firms or, more broadly, financial services is a strong plus. Strong SQL skills required. Familiarity with financial data platforms (such as Bloomberg, FactSet, Aladdin, eFront, Moodys), financial databases, and data manipulation techniques strongly preferred. Strong quantitative background required, with hands-on experience applying statistical, time-series, and optimization techniques using Python libraries (e.g., SciPy, Scikit-Learn, cvxpy, statsmodels) to portfolio construction and asset allocation problems. Deep understanding of investment management and portfolio composition strategies, with knowledge across asset classes including fixed income, public and private equity, and private credit. Demonstrated experience applying quantitative methodologies (including optimization, factor modeling, risk decomposition, and econometrics) to support portfolio construction, asset allocation, and investment decisions. Demonstrated ability to partner with business teams to convert AI-generated artifacts (e.g., prototypes, proofs of concept) into production-ready applications. Experience bridging the gap between rapid AI-developed prototypes to quality full-stack applications is highly valued. Proven ability to design, build, and scale application systems in data-rich environments including custom AI tools. Master's or Ph.D. (or equivalent experience) in a quantitative or engineering field such as Computer Science, Mathematics, Statistics, Econometrics, Financial Engineering, or a related discipline. 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Analytics & VisualizationBuild and refine analytic models, develop robust data pipelines and interactive dashboards, leveraging advanced Python, SQL, Dash and Power BI to translate complex data sets into actionable insights. Machine Learning & AI Employ statistical techniques, machine learning algorithms, and GPT-based solutions to improve market analysis, develop investment strategies, and enhance decision-making processes. Innovation & Continuous Improvement Proactively identify opportunities to upgrade capabilities and stay at the forefront of fixed-income analytics. Monitor industry trends, market developments, and new analytical tools to maintain a competitive edge. Project Coordination Oversee multiple projects simultaneously, ensuring timely delivery of high-quality results. Maintain meticulous attention to detail and effective communication throughout all stages of project execution. Numerate self-starter with a bachelor's degree in finance, Economics, Mathematics, Computer Science, Engineering, or a related field (Master's degree a plus) 3+ years of experience in portfolio analysis or investment management, with a strong preference for quantitative fixed-income experience. Must have hands-on experience with Python, SQL and familiarity with BI/visualization tools (Dash, Power BI, Jupyter Notebooks). Nice-to-have, Practical knowledge of machine learning and AI (including GPT-based models) and their applications in financial analysis. Preferred experience with BlackRock's Aladdin, Bloomberg, and Macrobond for data extraction, portfolio monitoring, and analytics. Tenacious problem-solving abilities with a focus on efficiency and effectiveness. Strong attention to detail and passion for learning. Excellent communication skills and the ability to work collaboratively in a fast-paced environment. Demonstrated interest in investments and a desire to delve into the intricacies of fixed-income markets.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618517245830", "isPrivate": false, "latlongs": "42.3555076,-71.0565364"}, {"id": 618518514634, "name": "Actuary- North American Specialty", "posting_name": "Actuary- North American Specialty", "location": "New York, New York, United States", "locations": ["New York, New York, United States", "Remote, Remote, United States", "Boston, Massachusetts, United States"], "hot": 0, "department": "Actuarial", "business_unit": "0116-GRS-Actuarial-US", "t_update": 1784324880, "t_create": 1784314560, "ats_job_id": "76876", "display_job_id": "2026-76876", "type": "ATS", "id_locale": "2026-76876-en", "job_description": "Support the North American Specialty (NAS) Environmental business's profit, growth and operational objectives by performing advanced actuarial pricing analyses. Portfolio analysis: in-depth reviews of the portfolio's composition and profitability Rating models: maintenance and enhancement of existing models and development of new models as necessary Parameter studies: periodic data-driven reviews of pricing parameters Clear communication of results of actuarial analyses to underwriters, finance, management, and claims personnel Participation in discussions with lead Underwriters and Claims personnel regarding profitability and strategic direction Participation in the reinsurance placement process as necessary Responding to ad hoc analysis requests from Underwriting, Claims, and senior management Bachelor's degree required; Master's degree preferred. Associateship or Fellowship in the Casualty Actuarial Society (ACAS/FCAS) or in Society of Actuaries (ASA/FSA) designation preferred or comparable education/designation with relevant experience. Minimum 5-7 years relevant experience required. Sound knowledge of actuarial techniques and standards, as well as other business operations including financial, underwriting, legal, statistics, claims, sales, etc. Advanced communication and interpersonal skills and ability to build relationships and interact effectively with others within and outside the organization. Ability to motivate and mentor peers and motivate and train subordinates. Advanced computing skills (MS Office Excel, SAS, etc.) with ability to build complex models.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "remote_local", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618518514634", "isPrivate": false, "latlongs": "40.7127753,-74.0059728"}, {"id": 618517740211, "name": "Underwriting Risk Modeler or Capital Modeler- Commercial Lines", "posting_name": "Underwriting Risk Modeler or Capital Modeler- Commercial Lines", "location": "Remote, Remote, United States", "locations": ["Remote, Remote, United States"], "hot": 0, "department": "Finance & Accounting", "business_unit": "3046-GRS-Global Risk-US", "t_update": 1784835720, "t_create": 1781549700, "ats_job_id": "76414", "display_job_id": "2026-76414", "type": "ATS", "id_locale": "2026-76414-en", "job_description": "Collaborate with other team members to achieve the following goals. Parameterize UW Risk excluding natural catastrophe risk Build and maintain UW risk models and output exhibits Develop new solutions and improvements for statistical models and processes used to calculate these inputs Maintain clear and concise documentation of methods and activities Implement timely and practical solutions to complex problems Validate model parameterization and model function Collaborate with Underwriting and Actuarial to understand the business and guide development of Risk Analytics tools that accurately reflect the business Communicate processes and parameterization results to stakeholders outside of the team Bachelor's degree or higher in Mathematics, Actuarial Science, Statistics, Finance, Economics, or similar required Minimum 5-7 years relevant experience required Very strong analytical skills with solid understanding of core casualty actuarial methods, techniques, and standards Expert in MS Excel and experience coding; Experience working with Visual Basic for 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.html_header_searchicon_disabled #top .av_header_border_disabled.av_bottom_nav_disabled .main_menu .menu>li:last-child>a .avia-menu-fx{padding-right:13px;-moz-box-sizing:content-box;-webkit-box-sizing:content-box;box-sizing:content-box;} div .logo{float:left;position:absolute;left:0;z-index:1;} .logo,.logo a{overflow:hidden;position:relative;display:block;height:100%;} .logo img{padding:0;display:block;width:auto;height:auto;max-height:100%;image-rendering:auto;position:relative;z-index:2;height:100%;height:auto;-webkit-transition:opacity 0.4s ease-in-out;transition:opacity 0.4s ease-in-out;} .main_menu{clear:none;position:absolute;z-index:100;line-height:30px;height:100%;margin:0;right:0;} .av-main-nav-wrap{float:left;position:relative;z-index:3;} .av-main-nav-wrap ul{margin:0;padding:0;} .av-main-nav ul{display:none;margin-left:0;left:0;position:absolute;top:100%;width:208px;z-index:2;padding:0;box-shadow:0 8px 15px rgba(0, 0, 0, 0.1);margin-top:-1px;} .av-main-nav ul li{margin:0;padding:0;width:100%;} .av-main-nav ul li a{border-right-style:solid;border-right-width:1px;border-left-style:solid;border-left-width:1px;} .av-main-nav ul li:last-child > a{border-bottom-style:solid;border-bottom-width:1px;} .av-main-nav li{float:left;position:relative;z-index:20;} .av-main-nav li:hover{z-index:100;} .av-main-nav > li > ul{border-top-width:2px;border-top-style:solid;} .av-main-nav > li{line-height:30px;} .av-main-nav li a{max-width:none;} .av-main-nav > li > a{display:block;text-decoration:none;padding:0 13px;font-weight:normal;font-size:12px;font-weight:600;font-size:13px;-webkit-transition:background-color 0.4s ease-in-out, color 0.4s ease-in-out, border-color 0.8s ease-in-out;transition:background-color 0.4s ease-in-out, color 0.4s ease-in-out, border-color 0.8s ease-in-out;} .av-main-nav > li > a{-webkit-transition:none;transition:none;-webkit-transition:background-color 0.4s ease-in-out, color 0.4s ease-in-out, border-color 0.8s ease-in-out;transition:background-color 0.4s ease-in-out, color 0.4s ease-in-out, border-color 0.8s ease-in-out;} #top .av-main-nav ul a{width:100%;height:auto;float:left;text-align:left;line-height:23px;padding:8px 15px;font-size:12px;min-height:23px;max-width:none;text-decoration:none;font-family:inherit;} #top .av-main-nav ul ul{left:-207px;top:0px;margin:0;border-top-style:solid;border-top-width:1px;padding-top:0px;} .av-main-nav li:hover ul ul{display:none;} #top .av-main-nav li:hover > ul{display:block;} .avia-menu-fx{position:absolute;bottom:-1px;height:2px;z-index:10;width:100%;left:0;opacity:0;visibility:hidden;} .av-main-nav li:hover .avia-menu-fx,.current-menu-item > a > .avia-menu-fx{opacity:1;visibility:visible;} .avia-menu-fx .avia-arrow-wrap{height:10px;width:10px;position:absolute;top:-10px;left:50%;margin-left:-5px;overflow:hidden;display:none;visibility:hidden;} .current-menu-item>a>.avia-menu-fx>.avia-arrow-wrap,.current_page_item>a>.avia-menu-fx>.avia-arrow-wrap{display:block;} .avia-menu-fx .avia-arrow-wrap .avia-arrow{top:10px;} .html_main_nav_header.html_logo_left #top .main_menu .menu>li:last-child>a{padding-right:0;} .main_menu .avia-bullet{display:none;} .avia-bullet{display:block;position:absolute;height:0;width:0;top:51%;margin-top:-3px;left:-3px;border-top:3px solid transparent!important;border-bottom:3px solid transparent!important;border-left:3px solid green;} .avia-arrow{height:10px;width:10px;position:absolute;top:-6px;left:50%;margin-left:-5px;-webkit-transform:rotate(45deg);transform:rotate(45deg);border-width:1px;border-style:solid;visibility:hidden;} .avia-menu-fx,#advanced_menu_toggle{-webkit-transition:all 0.3s ease-out;transition:all 0.3s ease-out;} .main_menu a{-webkit-transition:color 0.15s ease-out;transition:color 0.15s ease-out;-webkit-transition:background 0.15s ease-out;transition:background 0.15s ease-out;} @media only screen and (min-width: 768px) and (max-width: 989px){.responsive .main_menu ul:first-child > li > a{padding:0 10px;} .responsive .logo{float:left;} .responsive .logo img{margin:0;} .responsive .av_mobile_menu_tablet .main_menu .avia-menu{display:none;} } @media only screen and (max-width: 767px){.responsive #header_main .inner-container,.responsive .main_menu{position:static;} .responsive #top .logo{position:static;display:table;height:80px!important;float:none;padding:0;border:none;width:80%;} .responsive .logo a{display:table-cell;vertical-align:middle;} .responsive .logo img{height:auto!important;width:auto;max-width:100%;display:block;max-height:80px;} .responsive #header_main .container{height:auto!important;} .responsive .logo img{margin:0;} } #advanced_menu_toggle{position:absolute;border-radius:2px;height:46px;width:46px;line-height:46px;text-decoration:none;text-align:center;right:0;top:50%;margin-top:-23px;z-index:10000;border-style:solid;border-width:1px;font-size:30px;display:none;} @media only screen and (max-width: 989px){.responsive.html_mobile_menu_tablet .main_menu .avia-menu{display:none;} .responsive.html_mobile_menu_tablet .container #advanced_menu_toggle{display:block;} } @media only screen and (max-width: 767px){.main_menu .avia-menu{display:none;} .container #advanced_menu_toggle{display:none;} } } @media print{a,strong{color:black!important;} a{text-decoration:underline;} .container{width:100%;} .container{width:100%;margin:0 auto;} #header_main{border-bottom:0;} nav{display:none;} } @media all{::selection{background-color:#002663;color:#ffffff;} .header_color div,.header_color nav,.header_color span,.header_color a,.header_color img,.header_color strong,.header_color ul,.header_color li{border-color:#1a1346;} .header_color a,.header_color strong,.header_color strong a{color:#1a1346;} .header_color a:hover{color:#1a1346;} .header_color .avia-menu-fx,.header_color .avia-menu-fx .avia-arrow{background-color:#1a1346;color:#ffffff;border-color:#080124;} .header_color .avia-bullet{border-color:#1a1346;} .html_header_top .header_color .main_menu ul:first-child >li > ul{border-top-color:#1a1346;} .header_color .main_menu ul ul,.header_color .main_menu .menu ul li a{background-color:#fecf00;color:#1a1346;} .header_color .main_menu .menu ul li a:hover{background-color:#fecf00;} .header_color .main_menu ul:first-child > li > a{color:#1a1346;} #top .header_color .main_menu .menu ul li>a:hover{color:#1a1346;} .header_color .main_menu ul:first-child > li a:hover,.header_color .main_menu ul:first-child > li.current-menu-item > a,.header_color .main_menu ul:first-child > li.current_page_item > a{color:#1a1346;} #advanced_menu_toggle{background-color:#fecf00;color:#1a1346;border-color:#1a1346;} .avia_desktop #advanced_menu_toggle:hover{background-color:#1a1346;color:#ffffff;border-color:#1a1346;} .header_color .avia-arrow{background-color:#fecf00;} .header_color .avia-bullet{border-color:#1a1346;} #top .header_color a:hover .avia-bullet{border-color:#1a1346;} .container{width:100%;} .responsive .container{max-width:1260px;} #top #header .av-main-nav > li > a{font-size:14px;} } @media all{.WCAG-2-A{display:none!important;} @media (max-width: 767px){::-webkit-scrollbar{-webkit-appearance:none;} ::-webkit-scrollbar-thumb{background-color:rgba(0, 0, 0, .5);border-radius:10px;} ::-webkit-scrollbar-track{border-radius:10px;background-color:#ffffff;} } } @media all{*:focus{outline:1px dotted #808080!important;outline-offset:-2px!important;} .header_color .main_menu ul:first-child>li>a{color:#1a1446;font-family:'roboto-bold';font-size:16px!important;} .html_main_nav_header.html_logo_left #top .main_menu .menu>li:last-child>a{padding-right:13px;} .header_color .main_menu ul:first-child>li>a:hover{background:rgba(255, 255, 255, 0.8)!important;} .menu-item-has-children:hover{background:rgba(255, 255, 255, 0.8);} .main_menu .avia-menu-fx{display:none;} .main_menu .current_page_item a .avia-menu-text{border-bottom:1px solid #1a1446;padding-bottom:6px;} .main_menu .sub-menu,.main_menu .sub-menu li a{background-color:rgba(255, 255, 255, 0.7)!important;border:0;font-size:14px!important;font-family:'roboto-bold'!important;} .main_menu .sub-menu li a:hover{background-color:#e8e8e8!important;} .main_menu li.dropdown_ul_available>a{padding-right:30px!important;} .main_menu li.dropdown_ul_available>a::after{font-family:FontAwesome;position:absolute;left:auto;margin:0 5px;font-size:12px;} .main_menu li.dropdown_ul_available>a:hover::after{} #header_main{border:none;background-color:#ffd000;} .logo img{width:250px!important;margin-top:10px;} @media screen and (max-width:989px){#advanced_menu_toggle[data-av_icon]:before{font-size:30px;font-weight:normal;font-family:'FontAwesome'!important;} #advanced_menu_toggle{border-width:0px;} .container{padding:0 30px;} .responsive .logo{padding-top:10px;} } .main_menu .current_page_item a .avia-menu-text{border-bottom:0!important;} @media screen and (max-width:767px){.rem-arrow a:before{content:' '!important;} .responsive #top #wrap_all .container{width:92%;max-width:92%;} #advanced_menu_toggle{left:0;right:auto;border-width:0px;} .responsive #top .logo{margin:0 auto;width:150px;} .responsive .logo img{max-height:40px;margin:0 auto!important;} #header_main{border-top:0;} } @media screen and (min-width:1024px){li#menu-item-13649 ul.sub-menu{left:207px!important;} li#menu-item-13649.dropdown_ul_available>a::after{font-family:FontAwesome;position:absolute;left:auto;margin:0 5px;font-size:10px;} } #top a:focus{outline-offset:-2px!important;opacity:1!important;} .inner-container a:focus{outline-offset:-5px!important;} @media screen and (min-width:768px) and (max-width:1024px){.header_color .main_menu ul:first-child>li>a{font-size:12px!important;} } #top .main_menu .av-main-nav ul ul{border:0!important;padding-top:0px;position:static;display:block!important;border-bottom:1px solid #000!important;overflow:hidden;background-color:transparent!important;} #top .main_menu .av-main-nav ul ul li a{padding-left:35px;font-size:12px!important;padding-top:5px;padding-bottom:5px;background-color:rgba(255, 255, 255, 0.7)!important;} #top .main_menu .av-main-nav ul ul li a:hover{background-color:rgba(232, 232, 232, 0.7)!important;} .av-main-nav ul li:last-child>a{border:none!important;} #top .main_menu .av-main-nav ul ul{border-bottom:0px solid #000!important;} } .navbar{display: none!important;} .logo{padding-right:60px!important;} #menu-item-973:hover{background-color:rgba(255, 255, 255, 0.8) !important;-webkit-transition: background-color 300ms linear;-ms-transition: background-color 300ms linear;transition: background-color 300ms linear;} #menu-item-11981:hover{background-color:rgba(255, 255, 255, 0.8) !important;-webkit-transition: background-color 300ms linear;-ms-transition: background-color 300ms linear;transition: background-color 300ms linear;} #menu-item-1136:hover{background-color:rgba(255, 255, 255, 0.8) !important;-webkit-transition: background-color 300ms linear;-ms-transition: background-color 300ms linear;transition: background-color 300ms linear;} #menu-item-1435:hover{background-color:rgba(255, 255, 255, 0.8) !important;-webkit-transition: background-color 300ms linear;-ms-transition: background-color 300ms linear;transition: background-color 300ms linear;} #menu-item-3937:hover{background-color:rgba(255, 255, 255, 0.8) !important;-webkit-transition: background-color 300ms linear;-ms-transition: background-color 300ms linear;transition: background-color 300ms linear;} #menu-item-12966:hover{background-color:rgba(255, 255, 255, 0.8) !important;-webkit-transition: background-color 300ms linear;-ms-transition: background-color 300ms linear;transition: background-color 300ms linear;} .fa-brands{-webkit-font-smoothing: antialiased; font-style: normal; font-variant: normal; line-height: 1; text-rendering: auto;font-family: 'Font Awesome 6 Brands'} .position-details li{list-style-type: disc;} .header-wrapper{display:none!important;}.disability p {text-align:center!important;background-color:#F0F0F0!important; height:45px!important;padding-top:12px!important;} .disability a {color:blue!important;text-decoration:underline!important;} @media only screen and (max-width: 1325px){.disability p {height:67px!important;}} @media only screen and (max-width: 675px){.disability p {height:92px!important;}} @media only screen and (max-width: 480px){.disability p {height:114px!important;}}h4{margin-top: 5px;font-weight: 600;}