Top Healthtech Data Science Jobs

Develop and validate AI, machine learning, and deep learning solutions for healthcare and medical device applications. Build data pipelines, prepare datasets, engineer features, conduct experiments, evaluate model performance, and prototype internal tools. Collaborate with researchers, engineers, and product teams to integrate AI capabilities, document technical findings, and mentor junior engineers.

Develop and validate machine-learning models for drug discovery using chemical, biological, imaging, and phenotypic datasets. Perform exploratory analysis, data integration, quality assessment, and predictive modeling for compound activity, selectivity, target engagement, and screening outcomes. Collaborate with data engineers, machine-learning engineers, medicinal chemists, biologists, and research scientists to build reproducible workflows, interpret results, and translate scientific questions into actionable insights.

Supports data science and analytics teams by managing Jira requirements, backlogs, workflows, dashboards, model portfolios, and prioritization processes. Partners with technical teams, leadership, and stakeholders to communicate model status, risks, blockers, and priorities. The role also improves documentation and intake processes, facilitates prioritization decisions, and builds repeatable processes in a compliance-sensitive environment.

Build and productionize machine learning, NLP, generative AI, and analytics solutions for healthcare and regulated federal data. Responsibilities include data preparation, feature development, experimentation, model evaluation, error analysis, validation, workflow monitoring, troubleshooting, and translating stakeholder requirements into technical solutions.

Leads clinical data strategy and operations across studies, owning data collection, cleaning, database lock, risk-based data review, quality monitoring, analytics, and data integrity. Partners with clinical, statistical, medical, safety, regulatory, technology, and vendor teams to support inspection readiness, patient safety, protocol compliance, and timely trial delivery. Drives process improvements, influences stakeholders without direct authority, and coaches team members.

Develops and advances AI and machine learning solutions for digital pathology and multimodal clinical data. Builds, evaluates, validates, and deploys predictive models and clinically deployable products in collaboration with clinical, technical, regulatory, and software teams. Establishes practices for model quality assurance, reproducibility, monitoring, and regulatory documentation. Analyzes complex healthcare datasets, translates clinical needs into AI solutions, provides enterprise consultation, communicates insights, and mentors team members.

Participate in a 12-week data science internship by analyzing business problems, building dashboards and analytical models, using SQL, Python, and Power BI, collaborating with analytics teams, and presenting project outcomes to senior leadership. Interns will gain exposure to data engineering, governance, business operations, professional development, and cross-functional collaboration.

Full-time data science interns contribute to analytics projects, building dashboards and models with SQL, Python, and Power BI. They investigate diverse data sources, collaborate with analytics teams and business leaders, communicate findings, participate in professional development, and present project outcomes to senior leadership. The 12-week program includes mentorship, training, networking, and exposure to organizational operations.

Leads marketing measurement strategy and develops scalable frameworks for attribution, Marketing Mix Modeling, incrementality testing, experimentation, forecasting, and predictive analytics. Builds unified marketing data models, governs KPIs and tracking standards, creates executive reporting, and translates complex analyses into business recommendations. Partners cross-functionally with marketing, engineering, IT, privacy, and analytics teams while evaluating measurement technologies and vendors. Acts as the subject matter expert and helps scale the marketing analytics and data science function.

Leads technical support for VA healthcare AI citizen developers, developing and validating supervised, unsupervised, and reinforcement learning models. Builds synthetic healthcare data cohorts, designs secure cloud-based data science workflows, collaborates with federal stakeholders, interprets analytical results, mentors developers, and ensures model quality, documentation, privacy, governance, and regulatory compliance.