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

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

Applicant Tracking System Keywords

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

Hard Skills & Tools

statistical modelsmachine learningpredictive capabilitiesexploratory data analysisfeature engineeringmodel validationlogistic regressiontime seriesforecastingoptimization

Soft Skills

influence stakeholderscommunicate findingspresent insightstranslate business needsdrive consensusthought leadershipcollaborationstorytellinganalytical problem solvingbusiness strategy alignment