Top Senior Level Data & Analytics Jobs in Washington DC,

As a Market Intelligence Analyst, you will conduct market research and analysis of the semiconductor capital equipment market, develop financial models, provide strategic recommendations to senior leadership, and collaborate with various teams to implement market strategies and campaigns.

The Data Engineer will support a healthcare project by designing and delivering interactive dashboards and reports, integrating core data sources, and optimizing legacy systems. Responsibilities include developing ETL pipelines, creating actionable insights, and defining funnel metrics.

Seeking an experienced Research Scientist in Biophysics to develop and apply biophysical simulation techniques to generate actionable insights for drug discovery. Must have strong Python skills and a track record of innovation in simulation methods.

As a Senior Product Data Analyst, you will support the Product organization by curating data, uncovering insights, and creating dashboards. You will own the Product Analytics data catalogue, improve data quality, align the team around key metrics, manage experiments, and analyze product experience changes for better outcomes.

Senior Data Scientist role with a focus on full stack data science. Responsibilities include improving precision/recall of clinical algorithms, developing customer-facing analytics, and growing data science infrastructure. Ideal candidate has 5+ years' healthcare data science experience, ML Ops skills, and a product-focused mindset. Compensation includes $170K to $200K base salary + equity.

The VP Level Strategic Consultant will lead projects for pharmaceutical and biotechnology clients, providing strategic direction, overseeing project execution, and driving business growth. They will leverage extensive leadership experience to deliver high-impact results and tailored solutions for clients.

Design and implement enterprise-wide data strategies, manage data engineering assets, collaborate with cross-functional teams, ensure data integrity and security, develop data models, and lead data governance initiatives.