Director Data Scientist; Billerica MA
Listed on 2026-07-17
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IT/Tech
Data Scientist, AI Engineer (Applied/Software) -
Research/Development
Data Scientist
Work Your Magic with us! Start your next chapter and join EMD Electronics. Ready to explore, break barriers, and discover more? We know you’ve got big plans – so do we! Our colleagues across the globe love innovating with science and technology to enrich people’s lives with our solutions in Healthcare, Life Science, and Electronics. Together, we dream big and are passionate about caring for our rich mix of people, customers, patients, and planet.
That's why we are always looking for curious minds that see themselves imagining the unimaginable with us.
Everything we do in EMD Electronics is to help us deliver on our purpose of being the company behind the companies, advancing digital living. We are dedicated to being the trusted supplier of high‑tech materials, services and specialty chemicals for the electronics, automotive and cosmetics industries. We foster a global collaborative organization made up of individuals who have the passion to win, obsess about the customer, are relentlessly curious and act with urgency.
Together, we push the boundaries of science to make more possible for our customers.
The Director is a senior individual contributor and scientific authority responsible for shaping how real‑world evidence is generated and used to inform high‑impact development and regulatory decisions. This role combines deep statistical and quantitative expertise with strong scientific judgment to define key questions, evaluate methodological choices, and ensure outputs are credible, defensible, and decision‑grade. The Director plays a critical role in identifying methodological gaps, advancing approaches, and integrating perspectives across disciplines.
Key Responsibilities- Scientific & Strategic Leadership
- Define key scientific questions underpinning evidence strategies.
- Provide leadership on RWE approaches supporting development and regulatory decisions.
- Serve as a recognized scientific authority on complex methodological topics.
- Identify methodological gaps, risks, and opportunities, and define pragmatic forward paths.
- Methodological Expertise
- Critically evaluate study designs, analytical strategies, and data sources.
- Apply deep expertise in statistical theory, bias, confounding, causal inference, and quantitative modeling.
- Assess whether methodological choices are fit‑for‑purpose, transparent, and scientifically defensible.
- Guide complex methodological decisions involving multiple sources of evidence and competing analytical options.
- Decision Enablement
- Translate complex analysis into high‑impact, decision‑relevant insights.
- Shape evidence used to inform critical questions such as disease characterization, comparator strategy, endpoint feasibility, external control design, and patient population definition.
- Influence how evidence is generated and used in high‑stakes decisions across programs.
- Innovation, Methods & Data Integration
- Evaluate emerging methodologies, technologies, and data paradigms for relevance and impact.
- Evaluate and guide how real‑world data sources are selected, structured, and interpreted to support complex evidence needs.
- Apply deep understanding of data‑generating processes and data limitations to inform methodological choices.
- Shape how data is made accessible, interpretable, and usable for evidence generation across teams.
- Provide scientific input into data pipelines, transformations, and analytical workflows to ensure they align with study needs and methodological rigor.
- Partner with data science and engineering functions to ensure data infrastructure supports high‑quality, scalable, and reproducible analysis.
- Integrate innovations where they meaningfully improve rigor, efficiency, or interpretability.
- Cross‑Functional Collaboration
- Partner across clinical development, biostatistics, regulatory, medical, HEOR, and data science.
- Act as a bridge across disciplines, aligning scientific perspectives and decision needs.
- Influence without authority in a complex matrix environment.
- External Engagement
- Engage externally to support scientific credibility and methodological advancement.
- Contribute to methodological discussions with regulators, collaborators, or scientific communities where…
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