Top Remote Data Science Jobs in NYC, NY

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 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.

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, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

The Data Scientist 1 role involves cleaning and analyzing complex datasets, developing statistical models, and communicating insights through data visualizations. Responsibilities include collaborating with teams, maintaining data quality, and keeping up with advancements in the field.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

Build, validate, and productionize clustering and attribution heuristics on large multi-chain on‑chain datasets. Own end-to-end data pipelines, investigate edge cases (mixers, bridges, consolidation), benchmark against ground truth, and partner with investigations and product to define and defend precision/coverage metrics.

The Data Scientist II estimates, develops, and implements consumer credit models related to mortgage metrics and utilizes statistical methods and machine learning. This role involves cloud computing, data analysis, and communication of findings to nontechnical teams.

Embedded within a core business area, you will define problems, build metrics and reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end to improve growth, product, AI/automation, or partnerships.

Own the end-to-end analytical function for a business unit (growth, product, AI, or partnerships): define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions with stakeholders to deliver measurable business impact.

Embedded data scientist responsible for defining problems, building metrics and analyses, designing experiments, surfacing insights, and driving data-informed decisions across growth, product, AI/automation, or partnerships. Own end-to-end analytics, reporting, and stakeholder recommendations to improve key business metrics.

Embed with a core business area to define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end for product, growth, AI, or partnerships.

Embed within a business unit to define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI, and partnerships.

Embedded in a core business area, own analytics end-to-end: define problems, build reports, run analyses and experiments, surface insights, and drive data-informed decisions to improve key metrics.

The role involves developing graph algorithms, data pipelines for identity verification, and supporting data analysis for compliance products.

As a Senior Data Scientist, you will collaborate with cross-functional teams to drive AI/ML product development, analyze user data, and influence product strategies.

Perform statistical analysis, predictive modeling, and data visualization on workforce and training data. Build dashboards, produce ad hoc analyses and decision-support products, advise on data governance/privacy, and collaborate with stakeholders to define metrics, deliverables, and reproducible analytic workflows.

Use statistical and causal inference methods to build, implement, and monitor marketing models (Bayesian MMM, multi-touch attribution), analyze A/B and uplift tests, partner with marketing to test and drive data-informed decisions from large web-product datasets.

The Data Scientist will build predictive models, drive forecasting, design experiments, and translate findings for stakeholders, optimizing healthcare operations.

The Data Scientist I will analyze large datasets, build predictive models, conduct A/B testing, and communicate insights to stakeholders, enhancing business solutions.

The Data Scientist will develop and improve models and LLM systems for security applications, focusing on production readiness and experimentation. Responsibilities include building classifiers and evaluating models.

Contract data scientist to remotely gather, extract, and analyze technical information about AI models, benchmarks, data centers, and companies. Tasks include reading ML papers, tracking leaderboards, processing satellite images/permits, compiling infrastructure details, and producing data insights for research and policy. Part-time (10–30 hrs/week), flexible schedule with occasional Pacific Time meetings.