Senior Data Scientist I

Renishaw • Alpharetta, GA

3d • $95,300 - $158,800 • Onsite

About The Position

Would you like to apply advanced actuarial science and machine learning to build predictive models that directly influence underwriting, pricing, and risk decisions for insurers at scale? About the Business LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within Insurance, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. Our insurance risk solutions help drive better data-driven decisions across the insurance policy lifecycle – all while reducing risk. You can learn more about LexisNexis Risk at the link below. https://risk.lexisnexis.com/insurance About our Team The Insurance Analytics team are the trusted leaders in analytics excellence, delivering innovative, data-driven solutions through cutting-edge data science and strategic risk solutions to drive market leadership, impactful change, and lasting value for our customers and stakeholders. The team is responsible for new product innovation, model development, and creating actionable insights for our customers. We work closely with the Vertical and Product teams to design and implement new solutions for the insurance and OEM markets. By harnessing the power of data, our analytics team empowers insurers to make informed decisions, optimize risk segmentation, and enhance underwriting strategies, ultimately driving success in an ever-evolving insurance landscape. About the Role We are seeking a Senior Data Scientist I to join our Insurance Analytics team, with a strong foundation in actuarial science, statistical modeling, and data science. In this role, you will contribute to the development of innovative insurance products, advanced predictive models, and data-driven insights that inform key business decisions. You will partner closely with Product and Vertical teams to design and deliver analytical solutions that address complex insurance challenges and support evolving market needs. This role is ideal for someone who combines deep actuarial expertise with strong modeling intuition, is comfortable working with complex datasets, and can effectively translate analytical findings into clear, actionable recommendations that drive business and product outcomes.

Requirements

• Minimum undergraduate degree in relevant field and 4+ years of relevant work experience Or a master’s degree in a relevant field and 2+ years of relevant work experience. Or a PhD in a relevant field.
• Strong expertise in Python.
• Coding skills in R, SQL, ECL are a plus.
• Good foundation in actuarial science, including experience applying actuarial principles to pricing, risk segmentation, or model development.
• Strong foundation in statistical and mathematical modeling, including model assumptions, diagnostics, and interpretability. This includes linear and non linear models along with ML techniques.
• Extensive programming skills in Python and/or R, with extensive experience with their standard data manipulation and ML packages. pandas, scikit-learn, NumPy, XGBoost, PyTorch in Python and rpart, party, caret in R) and/or Scala.
• Strong ability as a self-starter to learn new technologies (Pyspark, ECL, Azure/AWS ML Services) and to share cross-functional knowledge across the teams nice to have.

Nice To Haves

• Able to build or test new processes with senior guidance.
• Domain expert in Data Science, Actuarial Science and/or Statistical Analysis to build advanced models and roll into production.
• Scopes and execute analytical approaches for moderately complex problems, seeking input where needed.
• Supports, maintains, and enhances existing models (e.g., GLM and tree-based methods).
• Applies statistical, mathematical, predictive modeling and analytical techniques to work with large, complex datasets from diverse sources.
• Independently prepares, cleans, and transforms data for analysis and modeling.
• Applies a range of data processing techniques and explores new methods to improve data quality and usability.
• Owns and delivers components of projects independently, including planning and execution of key tasks.
• Contributes to larger, more complex projects by executing defined workstreams and meeting timelines.
• Applies core data science and statistical methods within an insurance context.
• Strong foundation in actuarial science, including experience applying actuarial principles to pricing, risk segmentation, or model development.
• Understands and applies machine learning techniques, including hypothesis testing, sampling methods, model development (linear and non-linear), validation, and data pipelines.
• Takes initiative and ownership of work, proactively addressing challenges and identifying opportunities for improvement.
• Collaborates effectively with teammates, supporting a positive and accountable team environment.
• Balances innovation with practical business needs and team priorities
• Demonstrates accountability, follows through on commitments, and maintains high standards of work.
• Shows willingness to stretch beyond core responsibilities and support team success.

Responsibilities

• Developing and enhancing statistical and machine learning models using structured and unstructured data to generate predictive insights and attributes.
• Design and building data pipelines and analytical solutions that support risk segmentation and insurance use cases.
• Providing actuarial expertise and recommendations to inform model development, risk segmentation, and support rate filings.
• Researching and applying innovative data science methodologies to solve complex business problems.
• Managing and analyzing large, complex datasets, including data storage, processing, and quality assurance.
• Applying best practices for data validation, testing, and model performance monitoring.
• Collaborating with team members to share knowledge, strengthen capabilities, and contribute to a strong analytical culture.
• Identifying and leveraging new data sources to improve and validate existing models.
• Partnering with internal stakeholders to understand business needs, troubleshoot challenges, and deliver actionable insights.
• Maintaining a strong understanding of team tools, technologies, and evolving industry trends.
• Applying business and domain knowledge to drive effective, practical solutions.
• Communicating progress, insights, and outcomes clearly to stakeholders.
• Supporting team excellence by upholding high standards of quality, accountability, and execution.

Benefits

• Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
• Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
• Wellbeing: Wellness platform with incentives, Employee Assistance and Time-off Programs
• Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
• Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits
• Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
• This job is eligible for an annual incentive bonus.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior