Role: Data Science Product Manager
Location: Remote
Exp: 11+
Duration: Long Term
Employment: W2 or C2C
Overview:
We are seeking a Data Science Product Manager with a strong background in Life Sciences (Pharma/Healthcare/Biotech). The ideal candidate will bring hands-on data science expertise, deep knowledge of Real-World Evidence (RWE) data, and the ability to translate complex analytics into scalable, high-impact products. This role focuses on building data-driven solutions that support evidence generation, regulatory needs, HEOR, clinical development, safety, and commercial use cases.
Key Responsibilities:
Product Strategy & Ownership:
Own the end-to-end lifecycle of data science-driven RWE products from ideation to delivery and adoption.
Define product vision, roadmap, and KPIs aligned with pharma objectives such as evidence generation, faster insights, and cost reduction.
Translate business, clinical, and regulatory needs into product requirements and user stories.
Balance short-term deliverables with long-term platform scalability including datasets, models, and APIs.
Data Science & Advanced Analytics Leadership:
Collaborate with data scientists, statisticians, and engineers to design ML and analytics solutions.
Provide guidance on cohort design, feature engineering, modeling techniques, and validation approaches.
Ensure model interpretability, performance, and analytical rigor.
Act as a bridge between technical teams and business stakeholders.
Real-World Evidence (RWE) Expertise:
Lead development of products using RWE data such as claims, EHR, pharmacy, lab, registry, genomics, and digital health data.
Support use cases including HEOR, safety surveillance, regulatory submissions, clinical trials, and commercial insights.
Apply best practices in data quality, bias mitigation, confounding control, and transparency.
Stakeholder Engagement:
Collaborate with clinical, medical, regulatory, commercial, and IT stakeholders.
Conduct workshops, roadmap discussions, and product reviews with senior leadership.
Support governance and compliance discussions related to analytics and AI.
Governance, Compliance & Quality:
Ensure compliance with GxP, HIPAA, GDPR, and other regulatory standards.
Implement governance, documentation, auditability, and reproducibility in data science products.
Support audits and reviews of analytical methodologies and outputs.
Value Measurement & Improvement:
Define and track ROI metrics such as cost savings, study acceleration, and model reuse.
Monitor product performance and adoption to guide roadmap decisions.
Drive continuous improvement through feedback and experimentation.
Required Qualifications:
Experience:
8+ years of experience in data science, analytics, or product roles.
3 5+ years of experience in Pharma/Life Sciences.
Experience delivering RWE or analytics products in regulated environments.
Hands-on collaboration with data science and engineering teams.
Technical Skills:
Strong knowledge of statistics, machine learning, and healthcare analytics.
Experience with Python and/or R.
Strong SQL skills and experience with large datasets.
Familiarity with ML libraries such as scikit-learn, statsmodels, PyTorch, or TensorFlow.
Understanding of cloud platforms like AWS, Azure, Google Cloud Platform, or Databricks.
Domain Knowledge:
Deep understanding of RWE data sources and limitations.
Knowledge of epidemiology, observational studies, and causal inference.
Experience supporting regulatory-grade evidence preferred.
Product & Leadership Skills:
Strong product management skills including roadmap planning and prioritization.
Ability to lead cross-functional teams without direct authority.
Excellent communication skills to explain complex concepts to non-technical stakeholders.
Preferred Qualifications:
Advanced degree (MS/PhD) in Data Science, Statistics, Computer Science, Epidemiology, or related field.
Experience in AI/ML governance, explainable AI, or model risk management.
Exposure to regulatory bodies such as FDA, EMA, or HTA.
Experience building analytics platforms or reusable data science products.
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