Top Data Science Jobs in NYC, NY

As an AI Data Scientist, you will develop, validate, and test AI models, mentor juniors, and support project delivery in quantitative analytics.

As a Senior Manager in AI Data Science, you'll lead innovative solutions, manage project execution, mentor teams, and engage with clients to drive strategic initiatives.

As a Staff Data Scientist, you will lead complex marketplace problem-solving, architect ML systems, mentor teams, and drive data science strategy in partnership with engineering and product management.

Apply quantitative analysis, data mining, and statistical modeling to generate actionable product and business insights. Design and track core metrics, build dashboards and visualizations, collaborate with product, engineering, and design teams, and use AI tools and scalable analytical workflows to accelerate decision-making while ensuring methodological rigor and data quality.

As a Principal Associate Data Scientist, you will develop credit underwriting models using machine learning and statistical methodologies, collaborate with cross-functional teams, and contribute to innovative modeling practices.

As a Staff Data Scientist at Gusto, you will drive data-informed decision-making, lead projects, collaborate with teams, and mentor others in statistical analysis and experimentation.

The Senior Associate - Data Scientist will develop AI and machine learning solutions, focusing on model lifecycle management and delivering AI initiatives in collaboration with business teams.

Lead the Design of Experiments center of excellence, standardizing incrementality measurement, building testing infrastructure, and mentoring Data Scientists while optimizing customer experience and validating product initiatives.

Use advanced analytics, statistical methods, and machine learning to transform large datasets into actionable insights. Build data solutions and pipelines, perform exploratory analysis, create visualizations, validate models (including generative AI and NLP), collaborate with clients, mentor juniors, and maintain data quality to inform strategic decisions.

Lead data science initiatives within Data and Analytics Engineering to build predictive models, maintain data pipelines and lakes, apply ML/DL and generative AI, ensure data quality, coach teams, manage project timelines, and collaborate with stakeholders to drive data-driven business growth.

Lead company-wide standards for causal inference and Bayesian experimentation. Build frameworks mapping evidence to actionable confidence levels, design learning strategies for high-impact questions, institutionalize Bayesian practices, partner with engineering to ensure reliable instrumentation, mentor data scientists, and serve as escalation point for complex measurement problems like interference, selection bias, and network effects.

Lead measurement and decision systems for patient growth: own incrementality, design experiments, build LTV/retention/forecasting models, create trusted marketing metrics, partner with Engineering for measurement plumbing, diagnose performance shifts, influence channel allocation, and mentor growth analytics teams.

Lead product measurement strategy and complex evaluation for major product areas. Own experimentation standards, design causal and Bayesian analyses, build scalable measurement systems and dashboards, drive cross-team initiatives, mentor data scientists, and influence product decisions to improve mental healthcare outcomes.

Lead data strategy for Headway's finance and revenue systems. Build metrics frameworks, forecasts, and predictive models to measure collections loss, improve revenue infrastructure, ensure auditability/GAAP readiness, and translate findings into executive recommendations and cross-functional initiatives.

As a Principal Associate Data Scientist, you'll build and manage machine learning models for marketing efficiency, translating business goals into data solutions and collaborating with stakeholders.

As a Product Data Scientist, you will analyze user behavior, drive experimentation, build data tools, and collaborate across teams to influence product strategy and innovation at Whatnot.

As a Senior Manager, Data Scientist, you'll lead travel data analysis and machine learning projects to optimize hotel search and pricing systems, collaborating with cross-functional teams to enhance customer experiences and deliver impactful solutions.

The Director of Data Science role at Capital One involves leading a team to build data pipelines and machine learning models, leveraging technologies like Python and AWS to derive insights for improving customer financial decisions.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

The role involves analyzing fraud and risk data, defining KPIs, collaborating on anti-fraud strategies, and creating tools and dashboards for data accessibility at Whatnot.

As a Data Scientist Associate, you will develop AI solutions, support model lifecycle management, and collaborate with teams in a hybrid work environment.

The role involves managing data science projects focused on travel intelligence, leveraging machine learning and data analytics to improve customer experiences.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

Lead the Business Cards & Payments data science team to build and deploy ML solutions across the customer lifecycle. Partner with engineers and product managers, use Python, Spark, H2O, AWS and relational data to design, train, validate, and implement models that drive business outcomes and improve customer experience.

The Data Scientist II will lead RWE studies, derive insights from real-world clinical data, and contribute to methodologies using advanced statistical techniques and AI tools, collaborating closely with pharmaceutical partners.