Senior Advanced Analytics & Insights Manager

About the role

We are looking for a Senior Advanced Analytics & Insights Manager with 5+ years of experience to support high-impact analytics work across healthcare and life sciences. This is a hands-on role for someone who can work directly with complex healthcare datasets, apply data science methods, write strong SQL and Python, and translate analytical outputs into clear business recommendations. The ideal candidate will combine technical execution with consulting-style problem solving.

Responsibilities

• Lead analytics workstreams from business question definition through data analysis, modeling, interpretation, and final delivery.
• Work hands-on with large healthcare and life sciences datasets, including claims, provider, patient, market, commercial, or other real-world data.
• Write efficient SQL to extract, join, transform, validate, and analyze large datasets.
• Use Python for data wrangling, automation, statistical analysis, modeling, and repeatable analytical workflows.
• Apply appropriate data science techniques such as segmentation, forecasting, classification, regression, clustering, propensity modeling, or other statistical methods.
• Translate ambiguous client or business asks into structured analytical approaches, assumptions, outputs, and timelines.
• Build clear, client-ready deliverables in PowerPoint, Excel, dashboards, or other reporting formats.
• Perform QA on data, code, methodology, and outputs to ensure accuracy and defensibility.
• Support basic data engineering tasks such as dataset creation, data cleaning, feature generation, pipeline logic, and workflow automation.
• Partner with cross-functional teams across analytics, product, engineering, consulting, and client-facing functions.

Requirements

• 5+ years of experience in data science, advanced analytics, healthcare analytics, life sciences analytics, analytics consulting, or a related quantitative role.
• Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Economics, Public Health, or a related quantitative field.
• Strong hands-on SQL experience, including complex joins, CTEs, aggregations, window functions, data validation, and performance-aware querying.
• Strong hands-on Python experience using libraries such as pandas, NumPy, scikit-learn, statsmodels, or similar tools.
• Experience working with large, complex datasets and turning them into actionable insights.
• Practical understanding of data science methods and when to apply them to business problems.
• Basic understanding of data engineering concepts such as ETL/ELT, data pipelines, data models, data quality checks, and reusable workflows.
• Experience working in cloud-based or server-based analytics environments such as Databricks, Snowflake, AWS, Azure, GCP, or similar platforms.
• Strong communication skills with the ability to explain technical work to nontechnical stakeholders.
• Ability to manage multiple priorities, work independently, and maintain strong attention to detail.

Preferred Qualifications

• Experience in healthcare, life sciences, pharma, medtech, payer/provider analytics, commercial analytics, or real-world evidence.
• Experience with healthcare claims, EHR/EMR, provider, patient, HCP/HCO, prescribing, sales, market access, or similar datasets.
• Experience with scripting, Git/version control, notebooks, scheduled jobs, or workflow automation.
• Experience with Power BI, Tableau, Looker, Sigma, or similar BI tools.
• Exposure to cloud data platforms, scalable compute environments, or production-oriented analytics workflows.