Head of Data Science & Analytics Strategy

Merck & Co.

Cambridge (MA)

Hybrid

USD 191,000 - 300,000

Full time

14 days+

Application generator

Stand out for this role — generate a tailored resume and cover letter in about a minute.

Get past ATS filters

Job summary

HireLifeScience seeks a Director of Data Science (R-track) to lead enterprise analytics strategies and governance across therapeutic areas. You will guide KPI development, dashboards, and cross-functional decision-making, while ensuring scalable, compliant data pipelines and a culture of innovation.

Responsibilities include mentoring analytics teams, defending data quality, and driving adoption of AI/ML with modern visualization tools.

Qualifications

Bachelor's Degree in Computer Science, Statistics, Pharmacy, Nursing, Biological Sciences, or health care related discipline with a minimum of 10 years of experience in relevant field for job description, including:
Demonstrated aptitude of working with large datasets to transform into actionable insights, deep subject matter expertise in relevant discipline
People management skills
Programming and/or analysis experience may include SQL, Python, R, Databricks and the like.
Expert knowledge of statistics, data visualization, organizational skills, time management, and database concepts.

Responsibilities

Lead the development and execution of therapeutic-area data enablement and analytics strategies aligned with organizational goals.
Guide the creation of analytics KPIs and dashboards to monitor data performance, quality, and operational efficiency across therapeutic areas.
Serve as a key advisor to executive leadership, governance boards, and cross-functional leaders by translating analytical insights into strategic business decisions.
Maintain accountability for the design, performance, and integrity of automated data and analytics pipelines, ensuring scalability and compliance with regulatory standards.
Oversee analytics governance to ensure consistent application of standards, metrics, and quality controls across programs and platforms.
Drive adoption of emerging technologies (e.g., AI/ML, advanced data visualization, predictive analytics) and promote continuous improvement in analytical efficiency and value generation.
Define and enforce best practices for dataset design, feature engineering, and analytical evaluation to ensure comparability and reproducibility across studies.
Lead and mentor analytics team members, fostering an environment of innovation, accountability, and collaboration.
Strengthen organizational analytics maturity through targeted capability development and knowledge-sharing initiatives.
Partner with clinical, data management, and IT teams to ensure cohesive, interoperable analytics processes that drive meaningful business and scientific outcomes.
Champion organizational change; drive adoption of new operating models and digital capabilities across global functions