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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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 role may have in-office requirements depending on candidate location The Territory Modeling team in Complex Components is looking to hire a Data Scientist to help drive our mission of building best-in-class geographic risk segmentation models! Specifically, you'll conduct analyses & support modeling efforts on our internal & external geographic data using both traditional actuarial and cutting-edge data science techniques. Actuarial experience conducting analysis on insurance data, such as premium on-leveling, loss trending, loss development, etc. is highly preferred. Using SQL for wrangling structured data & curating analysis-ready data. Using Python for analyzing data, creating data visualizations, & conducting statistical analysis/modeling. Creating, testing, and deploying Generalized Linear Models (GLMs) used for predictive purposes, such as insurance pricing. Some experience/skills working with geographic data & GIS/spatial data science methods is great but not required. Achieved or currently pursuing Associateship or Fellowship in the Casualty Actuarial Society (ACAS/FCAS) designation. Solid knowledge of predictive analytics techniques and statistical diagnostics of models. Advance 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. 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Design and fine-tune large language/vision models to glean valuable insights from different kinds of unstructured data. Develop and adopt the best-in-class MLOps best practices throughout the data science lifecycle Applies knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions. Buildout in-house AI/ML products with other team members, including data scientists, IT developers, and business stakeholders Research and develop NLP, CV and other AI/ML models including LLMs, VLMs and GenAI applications to improve risk selection and pricing. 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. 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Design and develop solutions to support ingestion, curation and provisioning of complex enterprise data to achieve analytics, reporting, and data science Analyze, develop and execute data integration solutions, to manage the information lifecycle needs of an organization. Designs and builds data provisioning workflows/pipelines, physical data schemas, extracts, data transformations, and data integrations and/or designs using ETL and API microservices Builds data architecture and applications that enable reporting, analytics, data science, and data management and improve accessibility, efficiency, governance, processing, and quality of data. Improve speed to market by focusing on current data needs as well as building out long-term strategic data solutions using AWS, Snowflake, SQL, Informatica, as well as other modern data technologies Provide successful deployment and provisioning of data solutions to production or other required environments. Analyze complex technical problems and is expected to recommend process improvements that address complex technology gaps within a single business process and improve data reliability, quality, and efficiency Bachelor's or Master's degree in technical or business discipline or equivalent experience, technical degree preferred. Generally, 5+ years of professional data engineering experience Highly proficient in data engineering languages and tools, and strong proficiency in general programming languages and frameworks; ability to develop on multiple platforms. Required - Experience integrating Guidewire systems creating Data warehousing solutions in Snowflake for reporting, analytics, or data warehousing purposes, often using APIs and ETL tools. Extensive understanding of agile data engineering concepts and processes, such as CICD, pipelines, and iterative development and deployments Demonstrated experience delivering data solutions via agile methodologies on AWS, S3, Athena, Snowflake, IDMC ETL Requires critical thinking, data analysis, and data modeling experience Must be proficient in SQL and experience with Python and JavaScript Experience with ETL (Informatica PowerCenter/IDMC) and knowledge of variety of data platforms and ingestion patterns including eventing & streaming Demonstrate leadership and active pursuit of optimizing data, CI/CD process and tools, test frameworks & practices Must be proactive and self-driven, demonstrate initiative and be a logical thinker. Strong leadership, communication, collaboration skills with a track record of taking solution ownership Thorough knowledge in the following areas: Personal Line P&C insurance, general IT concepts, strategies and methodologies, thorough knowledge of new data architecture principles and concepts, thorough understanding of layered systems architectures, extensive knowledge of business operations, strategies and objectives.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://searchjobs.libertymutualgroup.com/careers/job/618504920181", "isPrivate": false, "latlongs": "43.0717552,-70.7625532"}, {"id": 618505565447, "name": "Princ Data Solutions Analyst", "location": "Remote, Remote, United States", "locations": ["Remote, Remote, United States", "Liberty Lake, Washington, United States", "Boston, Massachusetts, United States", "Portsmouth, New Hampshire, United States"], "hot": 0, "department": "Finance & Accounting", "business_unit": "0022-Corporate Finance-US", "t_update": 1753130280, "t_create": 1752605700, "ats_job_id": "71273", "display_job_id": "2025-71273", "type": "ATS", "id_locale": "2025-71273-en", "job_description": "Under minimal direction, prototypes/develops data solutions of high complexity to meet the needs of the organization and business customers. Designs proof-of-concept solutions utilizing an advanced understanding of financial insurance knowledge and multiple coding languages to meet technical and business requirements, with an ability to perform iterative solution testing to ensure specifications are met. Outstanding organizational skills and ability to manage multiple priorities while maintaining attention to detail and ensuring tasks are completed accurately and timely. Designs and develops data solutions that enables effective self-service data consumption and can describe their value to the customer. Assists stakeholders in defining metrics that are impactful to the business. Prioritize efforts based on customer value. Has a strong understanding of Agile techniques and demonstrated experience in fostering cross-functional collaboration between business and technology teams. Jira experience strongly preferred. Works with IT to help scale prototypes. Working with IT, assists in building robust systems focusing on long-term and ongoing maintenance and support. Ensures data solutions include deliverables required to achieve high quality data. 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Perform routine data investigations to profile and analyze data sets, addressing data quality and integrity issues. Build and implement tools to monitor data quality. Collaborate with Product Owners and Tech teams to establish new, and enhance existing, data pipelines into our Snowflake-based analytical warehouse. Manage security measures that enable data access restrictions. Define and document data element definitions, including associated metadata. Evaluate processes for gaps and inefficiencies, providing recommendations for improvement. Leverage data to solve business use cases, including packaging and communicating recommendations clearly and concisely. Design and execute iterative solution testing to ensure desired product specifications are met. 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Gather and document product requirements, clearly communicate requirements to stakeholders, and ensure accurate implementation. Act as the subject matter expert for the pricing program and assigned states, provide thoughtful recommendations that influence state decisions and help drive corporate strategy. Lead cross-functional workstreams and manage moderate to high complexity projects. Conduct complex analyses to drive and support business decisions; where necessary, conduct in depth research of competitor offerings and filings. Educate IT partners on business vision and plan, and both IT and business partners on the impact of changes. Independently manage project timelines, flag risks and develop contingency plans, escalate blockers as appropriate. Regularly update leadership and stakeholders on project progress, addressing concerns and managing communication channels. Lead job shadow discussions with less experienced analysts. Provides technical training and user support to business groups. Bachelor's degree in mathematics, economics, statistics, or other quantitative field Minimum 4 year's relevant work experience, typically 6 years. Master's degree beneficial. Advanced proficiency in Excel, PowerPoint, and statistical software packages (e.g., SAS, SQL, PowerBI, Snowflake). Must have strong planning, organizational, analytical, decision making and communication skills. 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Be the go-to expert for state-specific auto product strategy, delivering actionable recommendations that improve pricing, training, and overall product offerings. Lead and drive your own projects, managing work streams that have meaningful business impact. Collaborate closely with state teams, DSOs, IT partners, and product managers to align strategies and implement nationwide initiatives. Stay ahead of the competition by researching market dynamics, competitor filings, and customer needs to inform innovative product changes. Share your expertise by mentoring junior analysts, developing training materials, and leading sessions that empower your colleagues. Conducts moderate to high complexity analysis under general direction. As subject matter expert for assigned states, completes state reviews and similar work for basic states independently and for complex states or countrywide programs under general direction. Queries data to conduct ad hoc analysis of metrics and builds simple tools and queries for others to use. Provides recommendations to training and processes to manager. Provides complex analysis to help drive and support business decisions. Provides thoughtful recommendations to state teams on pricing, strategy, etc. Consults on complex business issues and design considerations. Educates IT partners on business vision and plan, and both IT and business partners on the impact of changes. Serves as point person for moderate to high complexity country wide implementations. Leads own work streams on medium to long-term or moderate to high complexity projects. May manage aspects of low to moderate complexity projects. Based on strong understanding of how competitor actions impact marketplace, distribution channel and customers, conducts in depth research of competitor filings utilizing various sources. Research may be at the state, competitor or countrywide level. 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Communicates clearly - effectively communicate (written & oral) findings, insights, and recommendations to various stakeholders & works collaboratively to recommend solutions and investigates product performance. Bachelor's degree in mathematics, economics, statistics, or other quantitative field. Minimum 3 years relevant work experience, typically 4 years. Strong proficiency in Excel, PowerPoint, and statistical software packages (e.g., SAS, Emblem). 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