Data Science Jobs in Cambridge, MA

Own long-term product strategy and roadmap for Circle's digital assets and capital markets platform. Lead cross-functional initiatives, manage regulatory and market risks, define forecasting and liquidity models, influence executives, and mentor product managers to scale global stablecoin and capital access infrastructure.

Design, develop, and validate advanced ML and quantitative models for pricing and market-making. Analyze large market and sports datasets, build scalable data pipelines and real-time algorithmic engines, deploy and monitor models in production, establish best practices for backtesting and evaluation, and mentor teammates to raise technical standards.

Lead the strategy and execution of real-world data capabilities, focusing on data lifecycle management, vendor relationships, and collaboration with various teams to deliver analysis-ready datasets.

Own strategy and roadmap for Crunchbase's customer-facing AI data layer. Identify and validate model-derived data products, lead cross-functional development, set quality standards, drive adoption and monetization, and monitor performance and product economics.

The role focuses on developing and implementing digital strategies using AI and automation in pharmacology and drug development, managing partnerships, and ensuring compliance with industry regulations.

As a Data Science Manager, you will lead a team in developing personalized experiences through machine learning, aligning efforts with product and engineering to drive impact and innovation.

Lead enterprise sales to pharma and biotech customers, owning the full sales cycle from prospecting to close. Build and manage strategic pipelines, navigate complex multi-stakeholder deals, engage technical and executive buyers, translate product value, and collaborate with founders, product, science, and customer teams to grow long-term partnerships.

Lead research and advisory work on data foundations for analytics and ML: produce 8–12 research assets annually, drive vendor evaluations (Forrester Wave), consult clients on data/AI strategy, present at events, support business development, and foster cross-team collaboration. Focus areas include data quality, governance, context-ready data, large-scale data management, and measuring business outcomes from analytics and ML.

Lead development and implementation of a legal digital and technology product framework to accelerate AI and data-driven solutions. Own product delivery, prioritize customer/user needs, collaborate with technology, UX, and leadership, and drive change-transformation artifacts (business case, change impact, communications, training). Measure success, optimize costs, and scale solutions across the Legal Department.

Lead enterprise-level strategy and delivery for building design, engineering, data readiness, and AI adoption. Define customer success plans, run workshops, shape consulting offerings, mentor staff, drive change management, and ensure high-quality project delivery and measurable customer value.

Lead the Oncology Data Science team in developing data-driven solutions for low molecular weight drug development, leveraging AI and machine learning. Collaborate with stakeholders to execute data science strategies and ensure adherence to best practices in analytics.

Lead data science projects to advance drug development, implementing models for patient selection and clinical trial optimization, and collaborating with cross-functional teams.

Lead Customer Success for enterprise HR clients by owning onboarding, engagement, renewal, and expansion. Build scalable onboarding and enablement, track customer health and ROI, facilitate executive workshops, and feed customer insights into product and GTM. Hire and develop a high-performing CS team and partner cross-functionally.

Lead finance analytics strategy owning data warehouse, BI, GCP cost optimization, and Finance AI automation. Build a reporting Center of Excellence, establish data pipelines and AI model foundations, enable self-service analytics, ensure data governance and audit readiness, and manage a team of engineers and a finance/strategy manager.

Lead end-to-end machine learning projects to improve customer engagement and retention. Build, test, and deploy models for user forecasting, personalization, and Casino engagement. Partner cross-functionally to scale solutions, mentor junior data scientists, and communicate model impact to influence product and marketing strategy.

Lead the product lifecycle for technology solutions in the biomedical field, integrating AI/ML and managing interdisciplinary product teams. Drive innovation, create user experiences, and oversee regulatory data management.

Own the acquisition product roadmap and engineering priorities to drive durable user growth. Define target audiences and channel mix, build product-driven acquisition mechanics (referrals, growth loops), enable channel effectiveness (discoverability, search/AI readiness, integrations, tracking), test new acquisition tactics, and align product investment with Performance Marketing, SEO, Partnerships, and Brand while measuring long-term subscriber value.

Lead and grow a Data Science team for Provider Products, set analytical direction, own experimentation and measurement, review methods, partner with product and engineering, hire and develop data scientists, standardize analytics and integrate generative AI to improve workflows and outputs.

Lead and mentor ML engineers and data scientists, overseeing ML strategy and development of scalable models for healthcare applications.

The Vice President of Biostatistics leads the statistical strategy for drug development in oncology, oversees clinical trial design, and manages external partnerships while ensuring regulatory compliance.

The Senior Director, Business Development will drive Cytel’s Pharma client relationships, create strategic sales plans, and oversee client-focused initiatives to expand business growth.

The Digital Engineering Data Solutions Architect will develop data architectures, support system lifecycle management, and collaborate on innovative solutions in national security projects.

Lead process sciences and innovation for mRNA and LNP platforms: scout and implement emerging technologies, design and run experiments to improve synthesis, purification and formulation, partner with Analytical Development on PAT and in-line monitoring, drive mechanistic understanding, mentor junior staff, and manage vendor and academic collaborations to advance scalable, high-quality manufacturing.

As a Lead Data Science Analyst, you will develop predictive models, conduct statistical analyses, and create AI-driven solutions to enhance GTM strategy and customer outcomes.

This role involves business development, client relationship management, project leadership, and team development in the life sciences consulting domain, focusing on delivering custom solutions for clients.