Data Scientist Jobs in New York, United States

DoorDash seeks experienced Data Scientists to lead analytics across multiple teams, driving data‑driven decisions in areas such as customer acquisition, fraud prevention, marketing, and marketplace efficiency. Candidates will design experiments, build dashboards, mentor junior analysts, and collaborate with engineering to implement data solutions.

Payments Data & Analytics- Data Scientist Associate is a role focused on leveraging data science, research, and business expertise to drive client‑centric innovation in cost‑based analytics and advanced GenAI applications for JPMorgan Chase Merchant Services.

Internal Audit at TikTok builds data products to enable continuous auditing and risk discovery across e‑commerce, ads, trust & safety, and more. The Senior Data Scientist designs data‑driven testing strategies, develops ETL pipelines, analytics frameworks and dashboards, and applies statistical and machine learning methods to surface risk signals.

Hearst Magazines seeks a Senior Data Scientist to lead the Data & AI team in New York. The role focuses on building advanced machine learning models that power personalized user experiences, next‑generation advertising, and actionable insights for editorial and commercial teams.

Director, Data Scientist - External Data Strategy at Capital One leads a team of 10-15 data scientists to build data pipelines, advanced analytics, and models that enable the company to understand customers' financial lives. The role partners with cross‑functional teams of data scientists, software engineers, and product managers to deliver data and insights that drive business decisions.

Bureau Data Strategy team at Capital One transforms raw credit bureau data into high‑impact underwriting insights. The manager leads a cross‑functional group of data scientists, engineers, and product managers to build and deploy machine‑learning models using Python, Spark, AWS and H2O, turning massive numeric and textual datasets into actionable products.

The Servicing Intelligence team at Capital One builds applied generative AI solutions on unstructured, multi-modal data (text, image, audio) to embed AI across frontline agent servicing, back-office document processing, regulatory compliance, and customer experience. As a Senior Associate, Data Scientist, you will apply open-source LLMs and VLMs, build and operationalize ML/NLP models, and define AI observability and monitoring controls for production systems serving 80+ million customers.

Macadam Technology Team builds innovative software solutions and data-driven products. The Jr Java Full Stack Developer/Software Programmer/Data Analyst/Data Scientist will develop Java web applications, design databases, analyze datasets, and create machine learning models to support business decisions.

Y Combinator [Sandbox] team seeks a Data Scientist to drive data-driven insights and build predictive models supporting portfolio companies. The role involves designing experiments, analyzing large datasets, and collaborating with engineers to integrate analytics into products.

Data Scientist role at Dropbox (Ats) focuses on leveraging large-scale data to drive product decisions and improve user experience. Candidates will analyze complex datasets, build predictive models, and collaborate with cross-functional teams across engineering, product, and design.

Zillow Group (Ats) Data Science team builds predictive models and analytics tools to improve real estate insights and customer experiences. The Data Scientist designs experiments, develops machine learning pipelines, and collaborates with engineers to integrate data products.

Confido is the AI infrastructure powering modern CPG, used by 200+ brands to unify finance, accounting, sales, and operations. As a Data Scientist in New York City, you'll build production-grade models for demand and sales forecasting, promotion effectiveness, and data quality evaluation, working alongside the AI/ML engineering team to ship insights directly inside the product rather than in slide decks.

Lightning AI, the company behind PyTorch Lightning, seeks a Data Scientist to drive decision-making as it becomes the first fully-integrated neocloud for AI training. This role partners with Product, Engineering, and Sales to analyze usage patterns, build data pipelines, and create dashboards that support growth.

Sunset is a data company that turns sensitive internal enterprise data into de-identified datasets while preserving structure and meaning, partnering with frontier AI labs. As the first Data Scientist focused on evaluation, you will establish how the company knows whether its data is actually getting better by building datasets, experiments, quality measures, and feedback loops.

Graphite builds modern code review tools for fast-moving engineering teams. The Data Scientist role drives product direction by analyzing 10TB of data, building scalable pipelines with DBT, Segment, and Redshift, and creating models and visualizations to inform decisions.

Bedrock Robotics team advancing autonomy for construction machinery. The Data Scientist leads high‑impact data science across autonomy, safety, and product, turning telemetry and operational data into actionable insights that shape engineering and product decisions.

Point72’s Cubist Systematic Strategies team seeks a Data Scientist to develop scalable, reliable data pipelines that support predictive modeling for systematic trading across equities, futures, and FX. The role involves sourcing new data sets, engaging vendors, building ingestion and cleaning tools, and performing descriptive analytics to uncover potential alpha signals. Candidates should hold a Ph.D. in a quantitative discipline, have at least one year of data science or quantitative research e

Data Scientist on Elsevier's Data Science team, advancing scientific discovery by building AI systems that reason over publications, datasets, knowledge graphs and ontologies. Designs, develops and deploys machine learning, NLP and generative AI solutions, creates retrieval and recommendation engines, fine‑tunes large language models, builds scalable pipelines and evaluation frameworks, and collaborates with engineering, product and domain experts.