Sr Data Scientist

We are seeking a Senior Data Scientist specializing in Machine Learning to join our Advanced Analytics team supporting clinical research and development. This role focuses on delivering high impact analytics that influence trial strategy and program decisions. The successful candidate will independently lead end to end analytical work—framing ambiguous questions, shaping data into analysis ready form, applying robust statistical and machine learning methods, and communicating insights clearly to stakeholders.
We are looking for someone with at least 4 years of professional experience as a data scientist/analyst in a pharma or related setting.
Key Responsibilities
• Lead complex clinical analytics: Own analyses across clinical studies and related data sources, tackling problems where the path is not predefined and the work requires strong judgment and rigor.
• Partner with stakeholders: Proactively engage clinical, biometrics, and cross functional partners to gather requirements, align on analytic intent, refine questions, and deliver decision ready outputs.
• Build statistical + ML solutions: Select, develop, and validate appropriate statistical approaches and machine learning models to answer clinical development questions; ensure interpretability and defensibility of results.
• Work with pharmacology-adjacent data: Integrate and analyze clinical outcomes with exposure/response or other pharmacology related datasets where relevant to the question.
• Engineer data at scale: Perform data wrangling, feature engineering, and reproducible pipelines in modern compute environments (Microsoft Fabric or similar); write production quality analysis code and adhere to team standards.
• Operate within clinical data standards: Work effectively within industry clinical data conventions and structured clinical data models; ensure analysis specifications and outputs align with quality expectations.
• Tell a clear story: Present compelling, validated narratives and visuals that translate complex analytics into insights stakeholders can act on.
• Be a team multiplier: Collaborate effectively, mentor where appropriate, and contribute to a culture of strong teamwork, responsiveness, and continuous improvement.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

• Demonstrated track record delivering analytics in clinical research settings, including working with late stage clinical datasets and typical clinical development constraints (e.g., endpoint complexity, protocol nuance, data quality realities).
• Strong foundation in statistical reasoning with practical experience applying predictive/ML methods in healthcare/clinical contexts (beyond academic exercises).
• Proficiency in Python or R, with the ability to handle large, complex datasets in distributed or cloud-enabled environments (e.g., Spark-based workflows).
• Comfort working within structured clinical data standards/models and producing analysis outputs that meet quality expectations in regulated environments.
• Strong communication skills: ability to explain methods, assumptions, and results clearly to both technical and non technical audiences.
• Highly collaborative with strong interpersonal skills; able to build credibility and maintain productive stakeholder relationships over time.

• Experience supporting programs in one or more of the following therapeutic domains: oncology, dermatology, hematology (or similarly complex disease areas).
• Experience with time-to-event or longitudinal modeling, and/or methods for explaining model outputs to non-technical partners (e.g., interpretable ML, model diagnostics, clear visualization).

Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.