Data Scientist Manager

Role Overview

• Lead complex, cross‑functional analytics initiatives from concept through execution, ensuring insights drive business strategy.
• Partner with senior leaders to define analytical problem statements, gather requirements, and translate business needs into data‑driven solutions.
• Act as a thought leader for data science best practices, analytic design, and modeling approaches across the organization.
• Influence stakeholders at all levels, presenting insights, use cases, and strategic recommendations.
• Develop and deploy advanced statistical models, machine‑learning tools, and predictive capabilities supporting LTC strategy and customer insights
• Conduct deep exploratory data analysis to uncover trends, relationships, and emerging insights that drive strategic action.
• Design and implement repeatable analytics pipelines, feature engineering strategies, and model validation frameworks.
• Build advanced datasets and analytical assets using SQL/SAS/Python/R; explore large, complex data environments.
• Develop subject‑matter expertise in policies, claims, customer behavior, and LTC data ecosystems.
• Contribute to data modernization projects, including cloud transitions, data engineering collaboration, and scalable data architecture improvements.
• Ensure data quality, model documentation, reproducibility, and governance standards are met.
• Communicate complex analytical findings through compelling written, visual, and verbal storytelling.
• Deliver clear, concise presentations that enable senior leaders to make informed decisions rapidly.

Requirements

• Bachelor’s degree in an analytical, quantitative, or technical discipline
• 5+ years business analytics and business support functions experience
• 5+ years of experience in one or more of the following statistical / analytic languages such as Python (Pandas, Scikit-Learn), Apache Spark (or PySpark), Hive, and Scala in a cloud computing environment
• 5+ years of experience in one or more of the following: database query and management tools (SQL, Spark, Preseto/Athena/Hive / HQL etc.)
• Hands-on experience with advanced analytics like logistic regression, time series, forecasting, optimization, and other predictive modeling techniques.
• ML experience and knowledge of ML platforms, libraries and programming
• Experience using GLMs, XGBoost and other predictive analytic techniques
• Ability to translate business needs into technical requirements and articulate analytic solution to get business buy-in
• Ability to influence decision makers and drive consensus

Tech Stack

• Apache
• Cloud
• Pandas
• PySpark
• Python
• Scala
• Scikit-Learn
• Spark
• SQL

Benefits

• Comprehensive Healthcare Coverage
• Multiple 401(k) Savings Plan Options
• Auto Enrollment in Employer-Directed Retirement Account Feature (100% employer-funded!)
• Generous Paid Time Off – Including 12 Paid Holidays, Volunteer Time Off and Paid Family Leave
• Disability, Life, and Long Term Care Insurance
• Tuition Reimbursement, Student Loan Repayment and Training & Certification Support
• Wellness support including gym membership reimbursement and Employee Assistance Program resources (work/life support, financial & legal management)
• Caregiver and Mental Health Support Services