Lead Data Scientist
$202,000–$323,000 year
RemoteUnited States
Job Summary
Lead complex data science initiatives across audience decisioning, marketing decision science, pharma direct measurement, and employer direct analytics to drive measurable business impact. Derive insights from large datasets to deepen understanding of user identity and the customer journey, building audience selection, segmentation, propensity, and lookalike models that ensure the right message reaches the right user. Partner with marketing and content teams on content generation, channel optimization, and attribution, while developing measurement capabilities for pharma direct partners using prescription, claims, and behavioral data. Support employer direct initiatives with member engagement modeling and refine attribution capabilities using NLP techniques to improve data quality at scale. Own the full lifecycle of predictive models, including problem framing, feature engineering, training, evaluation, deployment, and monitoring, while leading experimentation strategy with A/B testing and causal inference. Define the technical roadmap for decision science capabilities and provide technical leadership and mentorship to data scientists, ensuring rigorous decision-making and adherence to responsible AI best practices.
Required Qualifications
- 8+ years of experience in data science, machine learning, operations research, or a related quantitative field
- An undergraduate degree (or equivalent practical experience) in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, Operations Research, Data Science, or a closely related discipline
- Deep understanding of machine learning, statistical modeling, optimization techniques, causal inference, forecasting, experimentation, and predictive analytics
- Expertise in Python and common data science libraries (for example pandas, NumPy, scikit-learn, PySpark, TensorFlow, PyTorch, or similar)
- Strong working knowledge of databases and distributed data systems such as Redshift, PostgreSQL, and Spark/EMR
- Experience building and deploying solutions using cloud platforms (AWS, GCP, or Azure) and modern data platforms such as Databricks
- Experience deploying, monitoring, and operationalizing machine learning models using modern MLOps practices, including experimentation platforms, feature stores, and model monitoring
- Experience evaluating and applying AI/ML solutions, including generative AI and large language model (LLM) technologies, where appropriate
- Comfort with ambiguity and the ability to thrive in a fast-paced, high-change environment
- You are adaptable, intellectually curious, and open to new concepts, tools, and processes
- Strong communication skills, with the ability to influence technical and business stakeholders at multiple levels and to translate technical findings into clear, actionable recommendations for diverse audiences
- A collaborative, self-starting mindset
- You are a team player who can operate independently, take ownership, and hit the ground running
Desired Qualifications
- Experience in audience modeling, marketing analytics, attribution, or identity resolution
- Proven track record of technical leadership, influencing business strategy, and driving adoption of advanced analytical approaches across organizations
- Prior exposure to the prescription, pharmacy, or broader healthcare industry
- Experience with marketing analytics, audience segmentation, attribution, or incrementality measurement
- Experience supporting pharma manufacturer or employer and benefits partners in a B2B analytics context
- Experience with recommendation systems, reinforcement learning, optimization engines, or decision science applications
- An advanced degree (Master's or PhD) in a quantitative field
- Experience contributing to patents, publications, open-source projects, or industry thought leadership
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