Director, Data Science

JPA Health

18h

About The Position

The Director, Data Science leads advanced analytics initiatives across client engagements, developing and deploying technology-driven solutions using machine learning, artificial intelligence, and advanced statistical methodologies to drive insight and inform decision-making across complex healthcare challenges. In this role, you will design, implement, and oversee healthcare-focused analytical solutions that harness large-scale clinical, real-world, and commercial datasets. You will work closely with cross-functional teams to translate complex data into strategic impact for global biotech, pharmaceutical, and healthcare clients. As a senior technical leader, you will balance client delivery, innovation, and growth contribution while helping shape the future of data science capabilities within the organization.

Requirements

Master’s or Ph.D. in Data Science, Computer Science, Statistics, Bioinformatics, or a related field
6+ years of experience applying data science, machine learning, or advanced analytics in healthcare, life sciences, or related industries
Strong programming skills in Python and/or R
Demonstrated experience designing and deploying machine learning models, including regression, classification, clustering, decision trees, and recommender systems
Experience working with deep learning models such as LSTM, VAE, GAN, or large language models
Experience building time series models, forecasting approaches, or change-point detection methods
Experience working with large datasets in distributed or cloud environments (AWS, Spark, Hadoop, GPU computing, or similar)
Strong experience with data visualization and analytical libraries in Python, R, or related tools
Proven ability to lead complex technical initiatives from concept through execution
Collaborative mindset and ability to work across disciplines to deliver data-driven solutions

Responsibilities

Lead projects involving large, complex datasets, advanced statistical modeling, machine learning, artificial intelligence, and data visualization
Design and deploy predictive models to support strategic decision-making for healthcare and life sciences clients
Develop scalable, AI-driven analytical solutions using modern, open-source technologies
Define analytical approaches, simulation models, and feature engineering strategies across multiple healthcare domains
Validate, test, and refine models to ensure accuracy, robustness, and real-world applicability
Lead the design and optimization of data pipelines supporting clinical, real-world, and commercial data
Oversee data cleaning, transformation, and preprocessing workflows to support advanced analytics
Develop and implement distributed machine learning solutions across cloud environments
Ensure data architecture supports scalability, performance, and secure handling of sensitive healthcare data
Present complex analytical findings to internal teams, clients, and senior stakeholders
Translate technical outputs into clear, actionable insights for non-technical audiences
Provide technical leadership across analytics initiatives and mentor junior team members
Partner with cross-functional teams to support new business opportunities and innovation efforts
Contribute to new business and organic growth opportunities by shaping data science approaches for proposals, pitches, and client engagements