Senior Analytics Programmer

Job Title Senior Analytics Programmer / Data Scientist (Healthcare & Real-World Evidence)

We are seeking a highly skilled Analytics Programmer / Data Scientist to design, automate, and maintain data pipelines, perform advanced analytics, and deliver actionable insights across healthcare, pharmaceutical, and real-world evidence initiatives. This role will consolidate responsibilities currently distributed across multiple analytics, data science, and HEOR functions. The ideal candidate combines strong programming and data engineering skills with applied statistics, dashboard development, and the ability to translate complex data into clear business and clinical insights for internal and external stakeholders.

• Design, build, and automate scalable data pipelines integrating multiple first-, second-, and third-party data sources.
• Manage large datasets using SQL, Python, R, and cloud or database platforms (e.g., Snowflake, AWS, Linux environments).
• Implement data validation, quality checks, documentation, and reproducible workflows.
• Optimize performance, reliability, and maintainability of data infrastructure.

• Perform statistical analysis, modeling, and machine learning to support business, clinical, and market access decisions.
• Apply techniques such as regression, survival analysis, longitudinal analysis, and predictive modeling.
• Translate analytical findings into clear recommendations for decision-makers.
• Support ad-hoc analytical requests and recurring reporting needs.

• Build interactive dashboards and reports using tools such as Tableau, Power BI, Dash, or Shiny.
• Design KPI frameworks, metrics definitions, and automated reporting pipelines.
• Present insights to technical and non-technical audiences.

• Support real-world evidence generation, observational studies, and outcomes research.
• Assist with cohort definition, analytical plans, data extraction, and interpretation of results.
• Collaborate with clinical, medical, market access, and research teams.

• Own analytics projects end-to-end: scoping, timelines, execution, risk identification, and delivery.
• Communicate with stakeholders to clarify requirements and prioritize work.
• Provide mentorship or technical guidance to junior analysts when needed.

• Bachelor's or Master's degree in Data Science, Statistics, Biostatistics, Computer Science, Engineering, or related quantitative field (PhD or Pharm
  
  D a plus).
• 5+ years of hands-on experience in analytics, data science, or data engineering.
• Strong programming skills in Python and/or R.
• Advanced SQL experience working with large relational datasets.
• Experience building automated data pipelines and production workflows.
• Strong statistical foundation (regression, modeling, inference, visualization).
• Experience developing dashboards and reports (Tableau, Power BI, Dash, Shiny, etc.).
• Ability to communicate technical results clearly to business and clinical stakeholders.
• Strong organizational and problem-solving skills.

• Experience in healthcare, pharmaceutical, HEOR, RWE, or life sciences analytics.
• Cloud and data platform experience (AWS, Snowflake, Linux servers).
• Familiarity with SAS, Spark, or big data tools.
• Experience supporting observational studies or real-world data analysis.
• Exposure to machine learning workflows and model deployment.
• Client-facing or stakeholder management experience.

• Automated pipelines reduce manual reporting and analyst workload.
• Dashboards and analytics deliver reliable, timely insights to leadership.
• Data quality and reproducibility improve across projects.
• Stakeholders receive faster turnaround and clearer decision support.
• The role effectively replaces multiple fragmented analytics functions.