Top Data Scientist Jobs in NYC, NY

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.

Join Agentio's foundational data team to analyze behavior, model outcomes, run experiments, and build data and ML tooling to shape product decisions and improve measurement.

Join the Garner Health Intelligence team as a Data Scientist to enhance provider performance metrics, develop algorithms, design data pipelines, and collaborate cross-functionally to drive data-driven solutions for healthcare insights.

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 Data Scientist, you'll build and maintain portfolio systems, design risk frameworks, run backtesting experiments, and collaborate across teams to enhance portfolio analytics using AI-driven predictions.

The Data Scientist will collaborate with teams to develop AI features, build ML models, and translate complex data insights into business goals, leveraging technologies like Python and AWS.

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.

Develop, validate, and implement machine learning models using big-data tools and cloud platforms. Partner with engineers and product managers to translate analytics into production products, analyze large numeric and textual datasets, and communicate findings to drive business decisions for commercial banking portfolio forecasting.

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.

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.

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.

Work with clients and engineers to audit marketing datasets, build analytics pipelines, and apply predictive models (segmentation, attribution, propensity) using SQL, Python, cloud big-data tools, and ML frameworks. Support implementations, develop analytic applications, and communicate findings to drive marketing outcomes.

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 Director of Data Science, you'll lead a data science team to build generative AI solutions, leveraging machine learning and large-scale data analysis to enhance customer experience and drive business decisions.

The Senior Staff Data Scientist leads data-driven insights for product development and strategy in the investment sector, collaborating with cross-functional teams and optimizing portfolio performance.

Design and train LLMs and agentic systems for cybersecurity using RLHF/RLAIF and supervised fine-tuning. Build agent architectures, tooling, retrieval/memory, and evaluation pipelines with rigorous statistical benchmarking. Optimize prompts and inference, collaborate with engineers to productionize prototypes, and drive research on agent planning, safety, and reliability.

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

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.

The Data Scientist will analyze user behavior, create segmentation strategies, design experiments, and track business metrics to drive growth in a SaaS company.

As a Data Scientist Manager in Card Payment Fraud Prevention, you will lead a team to build and deploy machine learning models to combat first-party fraud, enhance customer safety, and optimize fraud capture rates by leveraging big data and advanced statistical methods.

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

The role involves leading a team to develop machine learning models for Travel Intelligence, focusing on the Hotels domain. Responsibilities include collaborating with cross-functional teams, leveraging technologies for data analysis, and delivering products that enhance customer experiences.

Lead and grow a marketplace growth analytics team to drive product and marketplace performance. Define success metrics, own experimentation strategy, deliver rigorous analyses (forecasting, causal inference, predictive modeling), partner with Product/Engineering/Finance, and translate insights into prioritized product decisions and reliable reporting. Balance strategic leadership with hands-on analytics and embed measurement into the product development lifecycle.