Clinical Data Scientist, Real World Evidence

Boston Scientific • Arden Hills, MN

9h • Hybrid

About The Position

The Clinical Data Scientist, Real World Evidence (RWE) will design and deliver advanced analytics solutions that generate robust, transparent, and scalable real-world evidence. This role operates with a high degree of autonomy across complex and ambiguous problems, leading sophisticated analyses, developing and validating novel methodologies, and operationalizing analytics across diverse real-world data sources. As a key contributor within the Global RWE function, this individual will lead analytic strategy for priority initiatives, serve as a subject-matter expert, and mentor team members. The role partners closely with scientific, clinical, regulatory, and data stakeholders to translate data into actionable evidence and advance RWE analytics capabilities across the organization.

Requirements

• Minimum Bachelor’s degree or advanced degree in data science, biostatistics, epidemiology, computer science, or a related field, or equivalent experience.
• Minimum of 8 years' with Bachelor’s degree experience or 5 years with a Master’s degree applying advanced analytics to real-world health care data, including electronic health records, claims, or registries
• Proven proficiency in modern data science tools and programming languages (e.g., Python, R, SQL)
• Demonstrated expertise in statistical and machine learning methods relevant to real-world evidence
• Proven experience communicating analytic findings to cross-functional and senior stakeholders (Clinical, R&D, Health and market access teams)

Nice To Haves

• Proven experience supporting regulatory-aligned evidence generation.
• Proven experience working in a global or matrixed environment.

Responsibilities

• Translate clinical and scientific questions into robust analytic plans and reproducible pipelines using EHRs, claims, registries, and other real‑world data.
• Lead data integration, causal inference, survival and comparative effectiveness analyses, feasibility assessments, and outcomes research with rigorous validation.
• Serve as analytic lead for priority studies, guiding study design and ensuring fit‑for‑purpose, regulatory‑aligned evidence.
• Develop and deploy advanced analytics, including predictive modeling, AI/ML, phenotyping, and NLP for unstructured data.
• Design clear data visualizations and dashboards to communicate insights.
• Partner with data engineering teams to enable scalable analytics environments and pipelines; lead pilots to assess new data sources and methods.
• Build reusable, version‑controlled pipelines with strong quality checks, documentation, and lineage.
• Implement validation and monitoring of data, analyses, and models over time.
• Contribute to data governance and champion reproducible research and code review best practices.
• Support interpretation and communication of results through reports, publications, presentations, and regulatory‑aligned materials.
• Present complex analyses clearly to technical and non‑technical stakeholders.
• Help resolve data and infrastructure issues supporting study execution.
• Partner cross‑functionally to align RWE analytics with organizational priorities.
• Act as a trusted analytic advisor influencing evidence strategy and prioritization.
• Mentor analysts and balance near‑term delivery with long‑term capability building.

Benefits

• The anticipated compensation listed above and the value of core and optional employee benefits offered by Boston Scientific (BSC) – see www.bscbenefitsconnect.com—will vary based on actual location of the position and other pertinent factors considered in determining actual compensation for the role.
• Compensation will be commensurate with demonstrable level of experience and training, pertinent education including licensure and certifications, among other relevant business or organizational needs.
• At BSC, it is not typical for an individual to be hired near the bottom or top of the anticipated salary range listed above.
• Compensation for non-exempt (hourly), non-sales roles may also include variable compensation from time to time (e.g., any overtime and shift differential) and annual bonus target (subject to plan eligibility and other requirements).
• Compensation for exempt, non-sales roles may also include variable compensation, i.e., annual bonus target and long-term incentives (subject to plan eligibility and other requirements).

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees