Senior Data Scientist - Specialty Operations

Position Summary

• Independently solves complex, ambiguous business problems and brings new perspectives to existing solutions across operational, financial, and clinical domains.

• Structures and leads advanced analytical and AI-driven approaches (e.g., predictive modeling, machine learning, optimization, forecasting, and emerging AI applications) to address high-impact business challenges.

• Partners closely with business stakeholders to understand objectives, constraints, and success metrics; translates these into scalable analytical solutions and actionable recommendations.

• Acts as an analytics product owner by defining problem statements, shaping solution approaches, prioritizing workstreams, and driving measurable business outcomes.

• Leads development of moderately complex solutions with meaningful business risk and visibility, ensuring rigor, explainability, and operational scalability.

• Develops and delivers executive-ready presentations that clearly communicate technical findings, trade-offs, and recommendations to senior leadership and client-facing teams.

• Applies strong knowledge of statistical methods, machine learning algorithms, and AI techniques to detect patterns, assess risk, and generate business insights.

• Uses advanced programming skills to explore, transform, and analyze large and complex datasets from multiple internal and external sources.

• Demonstrates strong consulting skills, including proactive problem identification, stakeholder alignment, and the ability to influence decision-making in cross-functional environments.

Required Qualifications

• 3+ years of analytics experience independently driving end-to-end analyses and initiatives with demonstrated business impact.

• 3+ years of data science experience, preferably in consulting or highly cross-functional environments.

• Experience in SQL and data visualization tools (e.g., Tableau or similar BI platforms).

• Experience programming in Python and/or R for data analysis, modeling, and solution development.

• Proven ability to communicate complex technical concepts clearly to non-technical audiences.

• Demonstrated ability to manage multiple priorities and deliver high-quality work in fast-paced, evolving environments.

Preferred Qualifications

• Strong knowledge of advanced analytics and AI techniques, including predictive modeling, machine learning, forecasting, optimization, and experimentation methodologies.

• Experience working with large, multi-source datasets in healthcare, pharmacy, or other regulated industries.

• Experience designing scalable analytical solutions that move from prototype to production.

• Anticipates risks, identifies roadblocks early, and proactively proposes mitigation strategies.

• Demonstrates executive presence and the ability to influence senior stakeholders and client-facing teams.

• Demonstrates depth in one or more specialized areas (e.g., forecasting, causal inference, NLP, AI applications, risk modeling) while maintaining broad applied data science capability.

Education

• Bachelor's degree or equivalent work experience in Mathematics, Statistics, ComputerScience, Business Analytics, Economics, Physics, Engineering, or related discipline.

• Master’s degree or PhD preferred