Data Scientist - Senior

Independence Pet Group•Scottsdale, IL

1d•Hybrid

About The Position

Independence Pet Holdings (IPH) is a corporate holding company managing a diverse portfolio of pet health brands and services. The Data Science team within Independence American Insurance Company (IAIC) is responsible for actuarial pricing, indications, and insurance-driven insights. This team ensures IAIC and IPH stay at the forefront of actuarial and pricing sophistication by evaluating new data sources, developing advanced analytical techniques, and delivering predictive insights. We are seeking a highly experienced Senior Data Scientist to join this team. This role is an individual contributor who leads complex data science initiatives, develops and maintains advanced predictive models, and partners closely with actuarial, business, and data teams. The Senior Data Scientist will serve as a technical leader on projects such as developing new rating variables and interactions, exploring novel modeling approaches to understand customer behavior, and supporting pricing, conversion, and retention analytics. This role plays a key part in shaping the direction and best practices of the R&D group, mentoring other data scientists, and strengthening the analytical culture across IPH.

Requirements

Graduate degree in Statistics, Mathematics, Actuarial Science, Data Science, or related quantitative field and 2+ years of experience in a data science or analytical role or 5+ years of progressive experience in a data science or analytical role.
Strong proficiency in Python, SQL, R, or other statistical programming languages for data manipulation, modeling, and analysis.
Strong foundation in statistical modeling and machine learning, with the ability to interpret and clearly communicate model results.
Ability to manage multiple priorities and projects in a fast-paced environment, both independently and collaboratively.
Able to engage and influence others with empathy and fostering trust.
Strong problem-solving, critical thinking, and attention to detail.
Excellent written and verbal communication skills, with the ability to influence across both technical and non-technical audiences.

Nice To Haves

Experience with SQL Server and/or Snowflake/Databricks.
Solid understanding of data warehousing concepts.
Hands-on experience with WTW Radar suite (Radar Base, Emblem) and/or Earnix.
Experience with data visualization tools such as Power BI, Tableau, or similar platforms.
Experience in Pet Insurance or P&C Insurance.

Responsibilities

Develop, enhance, and maintain predictive models (e.g., GLMs, machine learning, ensemble approaches) to support pricing, segmentation, and performance forecasting while balancing regulator considerations.
Lead exploratory data analysis to evaluate relationships between data elements and insurance processes, including pricing, conversion, retention, and risk segmentation.
Apply advanced statistical techniques to identify key drivers of sales, retention, and profitability, and forecast expected outcomes.
Translate complex technical findings into clear, actionable insights for both technical and non-technical audiences through presentations, reports, and visualizations.
Perform advanced root cause analysis using complex SQL and analytical techniques to investigate data inconsistencies and system issues; collaborate with Data Engineering and Business Units to resolve findings.
Design, implement, and maintain scalable data pipelines to collect, process, and integrate structured and unstructured data from internal systems and external data sources.
Lead data science projects end-to-end, owning analytical scope, methodology, timelines, and deliverables.
Serve as a technical lead on larger, cross-functional initiatives.
Create and maintain dashboards and reporting solutions (e.g., Power BI) to monitor key metrics such as rate level, risk segmentation, retention, and portfolio performance.
Mentor and develop analytics talent within the team and across the organization.
Stay current on industry trends, emerging technologies, and advancements in data science, analytics, and actuarial science.