Senior Data Scientist

Independence Pet Group

. Develop, enhance, and maintain predictive models (e.g., GLMs, machine learning, ensemble approaches) to support pricing, segmentation, and performance forecasting while balancing regulator considerations.

Posted 4/29/2026full-timeNew York City • Arizona, Illinois, New York • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Comprehensive full medical, dental and vision Insurance
Basic Life Insurance at no cost to the employee
Company paid short-term and long-term disability
12 weeks of 100% paid Parental Leave
Health Savings Account (HSA)
Flexible Spending Accounts (FSA)
Retirement savings plan
Personal Paid Time Off
Paid holidays and company-wide Wellness Day off
Paid time off to volunteer at nonprofit organizations
Pet friendly office environment
Commuter Benefits
Group Pet Insurance
On the job training and skills development
Employee Assistance Program (EAP)

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

predictive modelingGLMsmachine learningensemble approachesadvanced statistical techniquesSQLdata pipelinesdata analysisdata visualizationstatistical programming

Soft Skills

problem-solvingcritical thinkingattention to detailcommunicationcollaborationmentoringinfluencingempathyproject managementindependence