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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Applies knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions. Follows ML Ops best practices to create organized code repos, production-quality code, and reproducible results. Identifies and tests hypotheses, ensuring statistical significance, as part of building and developing predictive models for business application. Translates quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data. Enables the business to make clear trade-offs between and among choices, with a reasonable view into likely outcomes. Customizes analytic solutions to specific client needs. Regularly engages with the data science community and participates in cross-functional working groups. Solid knowledge of predictive analytics techniques and statistical diagnostics of models. Foundational/intermediate knowledge of predictive toolset; expert resource for tool development. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. Has a value-driven perspective with regard to understanding of work context and impact. Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience, a Master`s degree (scientific field of study) and 2 to 3 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and 4+ years of relevant experience.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "remote_local", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618513662547", "isPrivate": false, "latlongs": "37.09024,-95.712891"}, {"id": 618513647329, "name": "Assistant Director, Data Science", "location": "Boston, Massachusetts, United States", "locations": ["Boston, Massachusetts, United States", "Seattle, Washington, United States", "Remote, Remote, United States"], "hot": 0, "department": "Data Science", "business_unit": "3030-USRM-Insights & Solutions-US", "t_update": 1760128020, "t_create": 1759347540, "ats_job_id": "72497", "display_job_id": "2025-72497", "type": "ATS", "id_locale": "2025-72497-en", "job_description": "Apply knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets to generate insights to inform business decisions. Lead end-to-end development of new predictive models for high-impact business outcomes (e.g., improving claims handling efficiency): frame and test hypotheses, design statistically rigorous experiments, assemble/label training data, engineer features, and train/validate models. Build state-of-the-art ML systems that leverage structured data, unstructured text, and generative AI; select and implement appropriate algorithms and evaluation methods to deliver measurable accuracy and business value. Follow ML Ops best practices to create organized code repos, production-quality code, and reproducible results. Stay up-to-date with the latest advancements in data science and machine learning, and apply them to solving complex problems in the insurance claims domain. Provide technical mentorship and guidance to junior data scientists. Responsible for larger components of projects of moderate to high complexity. Communicate findings through technical presentations, reports, and recommendations to both technical and non-technical stakeholders. Participate in cross-functional working groups and contribute to the broader data science community to promote best practices. Broad conceptual understanding and practical knowledge of the end-to-end data science lifecycle. Exceptional hands-on data science technical skills (e.g. SQL, Python, and Statistical Inference). Experience collaborating with non-technical stakeholders to understand which problems need solving, design solutions, and bring them to market. Experience working with complex Type II data to assemble training datasets to appropriately model operational processes. Proficiency in Python and MLOps practices, with experience in version control (Git), code review, collaborative development workflows (e.g., GitHub/GitLab), and model versioning/experiment tracking (e.g., MLflow). Knowledge of claims handling processes and experience working with claims data. Experience developing LLM-based solutions for production use cases. Practical experience with cloud platforms like AWS (preferably), Google Cloud, or Azure. Familiarity with data pipeline and workflow management tools like Airflow, among others. Broad knowledge of predictive analytic techniques and statistical diagnostics of models. Expert knowledge of predictive toolset; reflects as expert resource for tool development. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. Networks with key contacts outside own area of expertise. Ability to establish and build relationships within the aligned functional area or SBU. Ability to give effective training and presentations to peers, management and less senior business leaders. Ability to use results of analysis to persuade team or department management to a particular course of action. Has a value driven perspective with regard to understanding of work context and impact. Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and 2 years of relevant experience, a Master`s degree (scientific field of study) and 4 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and 5+ years of relevant experience.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618513647329", "isPrivate": false, "latlongs": "42.3555076,-71.0565364"}, {"id": 618513607757, "name": "Director, Data Science - Property", "location": "Boston, Massachusetts, United States", "locations": ["Boston, Massachusetts, United States", "Remote, Remote, United States", "Columbus, Ohio, United States", "Seattle, Washington, United States"], "hot": 0, "department": "Data Science", "business_unit": "3030-USRM-Insights & Solutions-US", "t_update": 1760102040, "t_create": 1759240680, "ats_job_id": "72462", "display_job_id": "2025-72462", "type": "ATS", "id_locale": "2025-72462-en", "job_description": "Description The creative problem-solvers in Liberty Mutual's Insights & Solutions group harness the power of data, analytics and technology to develop innovative solutions that drive our US Retail Markets business forward and support a high-performing culture. This group brings together highly talented thinkers and doers ready to challenge the status quo and make an impact. As a member of this cross-functional group, you'll collaborate with teams across Liberty Mutual to deliver analysis that unlocks insights and sparks new, better ways of working. The Insights & Solutions team provides critical analysis through five functional groups within US Retail Markets. The US Retail Markets Data Science team brings together a diverse range of talent to predict future risk and what our customers will need to recover. Our data engineers write code that turns trillions of bits of information into structured data--data that our hundred-plus Data Scientists analyze with cutting-edge modeling techniques to unlock insights. From there, our tools and deployment teams ensure this data can be practically applied to business problems across US Retail Markets. Join us and be a part of this dynamic group driving industry-leading data segmentation, fueling the team's success now and into the future. This Director, Data Science oversees a team (3-5) of data science, advanced analytics, and actuarial resources. Specifically pushing the boundaries to bring cutting edge segmentation to the H3 (Property) Line of Business. This manager will be recognized as a thought leader for the team in terms of future research, in addition to managing analysts through the model build and rollout phases of the modeling lifecycle. This position requires deep knowledge of predictive analytics techniques, and advanced application of applying those techniques to business issues. About the role: Collaborates with business partners to collect innovation ideas, formally through Quarterly Process Improvement (QPE) meetings, and continuously. Partners across Product teams, USDS, and within Property and Specialty Product Design and Modeling (P&S PDM) team. Establish and maintain strategic partnerships within USDS and external teams to amplify project impact. Recognize when project progress is blocked and effectively communicate with team members and partners to resolve the obstacles and align on best next steps. Responsible for management, technical oversight and development for a team of data science, advanced analytics staff and actuarial talent Challenge the status quo from process to science, considering how we could improve & innovate throughout the Data Science Lifecycle. Once an improvement opportunity is identified, document & prioritize it to be acted upon. Support timely development and implementation of major pricing updates (ex. HMR 3). Following through with research ideas into the model build and rollout phases to ensure execution aligned with original intent. Provides strategic input on highly technically complex projects that drive change across USDS, P&S or Corporate Department. Directs work through others and may perform highly complex, technical and creative predictive analytics projects. Shapes the data science community and leads cross functional working groups. Qualifications Deep knowledge of predictive analytic techniques and statistical diagnostics of models. Expert knowledge of predictive toolset, to include highly technical tools. Proven ability to lead and drive projects and assignments to completion through others, to include prior experience effectively managing talent. Demonstrated ability to exchange ideas and convey complex information clearly and concisely, verbally, visually (presentations and exhibits), and in writing, consistent with the audiences and stakeholders with which s/he interacts. Ability to establish and build relationships within and outside the aligned functional area or SBU. Ability to give effective training and presentations to management and other groups. Presents to senior or functional department leaders or executives. Broad knowledge of business drivers and market context. Has a value driven perspective with regard to understanding of work context and impact. Competencies typically acquired through an advanced degree (in Statistics, Mathematics, Data Science or other relevant field of study) and 5 to 7 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) with 10 years of relevant experience. Insurance or financial services industry experience preferred. About Us Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role. As a purpose-driven organization, Liberty Mutual is committed to fostering an environment where employees from all backgrounds can build long and meaningful careers. Through strong relationships, comprehensive benefits and continuous learning opportunities, we seek to create an environment where employees can succeed, both professionally and personally. At Liberty Mutual, we believe progress happens when people feel secure. By providing protection for the unexpected and delivering it with care, we help people embrace today and confidently pursue tomorrow. We are dedicated to fostering an inclusive environment where employees from all backgrounds can build long and meaningful careers. By actively seeking employee feedback and amplifying the voices of our seven Employee Resource Groups (ERGs), which are open to all, we create an environment where every individual can make a meaningful impact so we continue to meet the evolving needs of our customers. We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/Benefits Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law. 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Collaborate with business stakeholders to deliver data products such as feature pipelines, predictive models, dashboards, and datasets derived from image data. Develop and maintain scalable data pipelines and model workflows, applying MLOps best practices for reproducibility, deployment, and monitoring. Research and prototype new methodologies for training, evaluating, and improving deep learning models, particularly for computer vision. Integrate model outputs into business applications and partner with engineering teams to operationalize models in production environments. Contribute to the design, construction, and validation of large and complex datasets in collaboration with cross-functional science teams. Communicate findings through technical presentations, reports, and recommendations to both technical and non-technical stakeholders. Participate in cross-functional working groups and contribute to the broader data science community to promote best practices. Demonstrated expertise in deep learning with an emphasis on computer vision. Strong foundation in machine learning, statistics, experimental design, and model evaluation metrics. Proficiency in Python and MLOps practices, with experience in version control (Git), code review, collaborative development workflows (e.g., GitHub/GitLab), and model versioning/experiment tracking (e.g., MLflow). Proficiency in deep learning frameworks such as PyTorch (preferred) or TensorFlow, with experience in model design, training, and deployment. Experience building and managing pipelines with workflow orchestration tools (e.g., Airflow, Luigi). Experience with Docker and CI/CD pipelines. Experience with container orchestration systems such as Kubernetes. Understanding of GPU acceleration, distributed training, and model optimization techniques (e.g., mixed precision, pruning, quantization). Experience with multimodal learning, including vision-language models and cross-modal representation learning. Track record of advancing research projects from ideation to implementation. Broad knowledge of predictive analytic techniques and statistical diagnostics of models. Expert knowledge of predictive toolset; reflects as expert resource for tool development. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. Networks with key contacts outside own area of expertise. Ability to establish and build relationships within the aligned functional area or SBU. Ability to give effective training and presentations to peers, management and less senior business leaders. Ability to use results of analysis to persuade team or department management to a particular course of action. Has a value driven perspective with regard to understanding of work context and impact. 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Be part of a growing community of data science professionals that harnesses the power of data to analyze performance trends, identify opportunities, and keep Liberty Mutual moving forward. The details Calling all aspiring data scientists! Here's the perfect opportunity to grow your knowledge and skills in key areas such as computer vision, GenAI, machine learning, and various modeling techniques and software. In this 11-week Data Science Graduate Summer Internship Program, you'll build robust models and use statistical software, such as R, Python, and SAS, to solve critical business problems in product management, claims, distribution, marketing, HR, legal, finance, and other business functions. At the conclusion of your summer internship, you'll deliver a presentation of your work and skills to your colleagues and the data science management team. The Data Science Graduate Summer Internship Program may be your first step toward pursuing a rewarding career at Liberty Mutual, one of the leading property and casualty insurers in the United States. Our interns often transition into full-time data scientists at our Boston Headquarters. Note: We encourage interested candidates to apply promptly, as the role may be unposted once we've received a sufficient number of candidates. We conduct interviews and extend offers on a rolling basis. Qualifications What you've got You possess proven statistical, mathematical, computational, and analytical skills, which you are acquiring through the pursuit of a Master's degree or Ph.D. in Mathematics, Statistics, Data Science, Economics, Operational Research, Computer Science, or a related field. You have completed doctoral qualifying exams (preferred). You have a record of academic achievement. You demonstrate solid oral, written, communication, and interpersonal skills. You are a whiz at statistical software, such as R, Python, and SAS. Programming skills are highly desirable. About Us Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications, and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role. As a purpose-driven organization, Liberty Mutual is committed to fostering an environment where employees from all backgrounds can build long and meaningful careers. Through strong relationships, comprehensive benefits, and continuous learning opportunities, we seek to create an environment where employees can succeed, both professionally and personally. At Liberty Mutual, we believe progress happens when people feel secure. By providing protection for the unexpected and delivering it with care, we help people embrace today and confidently pursue tomorrow. We are dedicated to fostering an inclusive environment where employees from all backgrounds can build long and meaningful careers. By actively seeking employee feedback and amplifying the voices of our seven Employee Resource Groups (ERGs), which are open to all, we create an environment where every individual can make a meaningful impact so we continue to meet the evolving needs of our customers. We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/Benefits Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law. 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Explore and experiment with emerging AI and Machine Learning technologies, including generative AI, NLP/NLU, computer vision, and trends in insuretech, fintech, and the sharing economy. Develop and iterate on prototypes using Python, thriving in a fast-paced R&D setting with a start-up mentality. Build custom algorithms, uncover data-driven insights, and share findings with the team and stakeholders. Continuously sharpen your skills by embracing new technologies and participating in hackathons, meetups, and other learning opportunities. Passionate about technology, innovation, and collaborative problem-solving. Curious and proactive in exploring new trends and tools in AI/ML. Excited to work in an environment where your ideas and contributions may shape real products. Eager to make an impact through hands-on prototyping, algorithm development, and data analysis. Working towards a Bachelor's, Master's or PhD Degree in Data Science, Engineering, Computer Science, Mathematics, Statistics or other relevant field Strong technical, analytical, communication and organizational skills A strong academic record with a cumulative 3.0 GPA preferred Must be able to work full-time from January - June 2026", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "hybrid", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618506221624", "isPrivate": false, "latlongs": "42.3555076,-71.0565364"}, {"id": 618513596284, "name": "Director, Data Science", "location": "Remote, Remote, United States", "locations": ["Remote, Remote, United States"], "hot": 0, "department": "Data Science", "business_unit": "3030-USRM-Insights & Solutions-US", "t_update": 1760102040, "t_create": 1759163040, "ats_job_id": "72450", "display_job_id": "2025-72450", "type": "ATS", "id_locale": "2025-72450-en", "job_description": "Oversee the management, technical oversight, and development of a team of data science professionals focused on tactical pricing strategies. Collaborate with business partners to both ensure appropriate reaction to emerging trends and proactively identify areas of concern. Establish frameworks outlining decision-making processes to drive the identification and evaluation of tactical pricing opportunities. Support the implementation of tactical pricing changes, ensuring robust consultation and collaboration across the org regarding state-specific opportunities. Engage with stakeholders to discuss state-specific opportunities and triage actions. Deep knowledge of predictive analytic techniques and statistical diagnostics of models. Expert knowledge of predictive toolset, to include highly technical tools. Proven ability to lead and drive projects and assignments to completion through others, to include prior experience effectively managing talent. Demonstrated ability to exchange ideas and convey complex information clearly and concisely, verbally, visually (presentations and exhibits), and in writing, consistent with the audiences and stakeholders with which s/he interacts. Ability to establish and build relationships within and outside the aligned functional area or SBU. Ability to give effective training and presentations to management and other groups. Presents to senior or functional department leaders or executives. Broad knowledge of business drivers and market context. Has a value driven perspective with regard to understanding of work context and impact. Competencies typically acquired through an advanced degree (in Statistics, Mathematics, Data Science or other relevant field of study) and 5 to 7 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) with 10 years of relevant experience.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "remote_local", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618513596284", "isPrivate": false, "latlongs": "37.09024,-95.712891"}, {"id": 618513618787, "name": "Senior Data Engineer \u2013 Cloud Data Warehousing (Investments Technology)", "location": "Boston, Massachusetts, United States", "locations": ["Boston, Massachusetts, United States"], "hot": 0, "department": "Technology", "business_unit": "0027-LM Technology-US", "t_update": 1760102220, "t_create": 1759266180, "ats_job_id": "72482", "display_job_id": "2025-72482", "type": "ATS", "id_locale": "2025-72482-en", "job_description": "Work in a Data and Analytics squad to design and build robust data pipelines that deliver high-quality insights to our investment teams. Collaborate with diverse teams of data engineers and product partners who believe in continuous learning, respectful collaboration, and inclusive data solutions. Build and optimize scalable, reliable, high-performance automated data pipelines and solutions using Snowflake and AWS. Drive data quality, governance, and observability practices throughout the development lifecycle. Stay current with industry trends and best practices in data engineering and recommend improvements to existing processes. Contribute to a culture of learning by mentoring junior engineers, participating in code reviews, and promoting engineering excellence and best practices. A bachelor's degree in technical or business discipline, or equivalent experience. 5+ years of experience in data engineering, with designing, building, and optimizing scalable data pipelines and architecture. Design and build data provisioning workflows/pipelines, extracts, data transformations, and data integrations using Snowflake cloud-native features in an AWS cloud environment. Intermediate experience using Python for data transformation, integration, and automation. Hands-on experience with modern public cloud-based data platforms--Snowflake, AWS (e.g., S3, Glue, Lambda). Proficiency with ETL/ELT pipelines and patterns for loading data warehouses and data lakes. Hands-on experience building and deploying CI/CD pipelines (e.g., GitHub Actions, Bamboo, or similar tools). Exposure to the Investments or Finance domain is highly desirable. Familiarity with building and consuming APIs (e.g., REST, API Gateway). Awareness of security best practices, including access control, authentication, and secure processing.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618513618787", "isPrivate": false, "latlongs": "42.3555076,-71.0565364"}, {"id": 618504971874, "name": "Enterprise Data Governance Leader", "location": "Boston, Massachusetts, United States", "locations": ["Boston, Massachusetts, United States", "Seattle, Washington, United States", "New York, New York, United States", "Plano, Texas, United States", "Remote, Remote, United States", "Columbus, Ohio, United States", "Portsmouth, New Hampshire, United States"], "hot": 0, "department": "Data Science", "business_unit": "3042-Enterprise Transformation & Solutions-US", "t_update": 1760102040, "t_create": 1750084140, "ats_job_id": "70752", "display_job_id": "2025-70752", "type": "ATS", "id_locale": "2025-70752-en", "job_description": "Shape the vision: Bring a strong point of view on what effective data governance looks like, grounded in industry perspective, internal context, and practical tradeoffs. Champion the evolution and adoption of our Enterprise Data Governance Playbook, ensuring alignment with compliance, risk, and business objectives. Drive execution: Run governance like a program, with defined workstreams, clear ownership, and success measures. Influence and align: Provide structure and clarity in moments of ambiguity, and help end circular debates by driving decisions to closure. Facilitate Data Governance leadership discussions, build alignment on key data policies, standards, and decision-making frameworks, and clear roadblocks by bringing facts, decisions, and recommendations to the right senior leaders. Connect the dots: Actively identify where business units are solving similar problems and facilitate targeted peer connections--not more meetings, but real collaboration. Help us scale these connections by partnering with our training experts to elevate and drive adoption of our standards, platforms, and best practices. Communicate value: Ensure governance efforts are well understood, appropriately scoped, and connected to business impact. Explain the \"why\" behind governance requests, set expectations, and build enterprise-wide support by telling a compelling story. Director II, Data Management (STP) $160,500 - $226,000. Annual FTO days (Flexible Time Off): 20 Strong written and oral communication skills required Experience in communicating recommendations to senior business leaders preferred BA/BS, or relevant work experience, in Computer Science or related field preferred MBA or advanced degree in Mathematics, Computer Science, Engineering, Economics, or other quantitative discipline strongly preferred 7-10 years of experience working in coding methodologies and design principles, particularly in open source tools and technology 3-5 years in data governance leadership strongly preferred Ability to work EST", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618504971874", "isPrivate": false, "latlongs": "42.3555076,-71.0565364"}], "debug": {}, "count": 174, "countFilterByMatchScore": null, "location_user": "any", "location_used": "", "locationInsights": null, 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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;} 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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 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(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;}