Director of Data Science (Remote Eligible)

$150,000 - $200,000/Yr

Mathematica Policy Research - Concord, NH

Full-time - Senior

Hybrid - Concord, NH

Professional, Scientific, and Technical Services

About the position

The Director of Data Science at Mathematica will lead a team of data scientists within the Health Solutions and Insights division, focusing on developing AI/ML solutions to address critical healthcare challenges using real-world data. This role involves defining the strategy and offerings for the practice, ensuring high-quality delivery of solutions, and fostering a culture of innovation and continuous growth while promoting diversity, equity, and inclusion within the team.

Responsibilities

• Direct the Data Science Practice within the Health Solutions and Insights division, leading a growing team of 20+ data scientists in applying cutting-edge data science methods to real-world health data.
• Develop and drive the practice vision, strategy, and offerings around innovative AI/ML solutions that furthers Mathematica's mission to improve decision-making in healthcare through the rigorous use of data and evidence.
• Direct projects, tasks, and initiatives involving cross-functional teams of data scientists, solution architects, engineers, researchers, and consultants to develop and deploy AI/ML solutions.
• Prioritize, budget, and manage practice investments, such as initiatives, conferences, trainings, white papers, and journal articles.
• Collaborate with external clients, partners, contractors, and community members.
• Mentor practice staff and elevate them as thought leaders.
• Lead change management efforts to create a culture of continuous growth and innovation.
• Actively support the advancement of organizational diversity, equity and inclusion efforts, and apply diversity, equity and inclusion lens across job responsibilities.

Requirements

• Minimum of 7-10 years of leadership experience in data science and analytics, with a strong focus on healthcare.
• Advanced degree (PhD or Master's) in Data Science, Computer Science, Economics, Public Health, Statistics or a related field.
• Experience with applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc.
• Strong understanding of multivariable calculus and linear algebra fundamentals for predictive performance and algorithm optimization techniques.
• Knowledge of unsupervised and supervised machine learning methods such as clustering algorithms, decision trees, and neural networks.
• Knowledge of generative AI technologies and techniques, including retrieval augmented generation, prompt engineering, and LLM fine-tuning.
• Knowledge of programming languages like Python, R, Julia, and SQL; experience with Scala, Java, or C++ is a plus.
• Experience architecting cloud-based solutions and leveraging cloud-based distributed computing with AWS; experience with GCP or Microsoft Azure.

Benefits

• Competitive salaries
• Comprehensive benefits package
• Employee stock ownership plan (ESOP)