Top Remote Data Science Jobs in NYC, NY

The Data Scientist II will design, build, and deploy machine learning models and data products, translating business problems into data-driven solutions, while collaborating with various stakeholders and ensuring reliable, production-ready outcomes.

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.

Seeking a skilled Data Scientist/Machine Learning Engineer to develop machine learning models, design AI systems, and collaborate in data analytics. Responsibilities include productionizing models, data engineering, and cross-functional collaboration.

Analyze large-scale educational data to inform product design and efficacy. Develop, evaluate, and maintain statistical and AI models, collaborate with cross-functional teams, communicate findings to stakeholders, and leverage AI tools for analysis and feature engineering while following software development practices.

Drive product and business analyses across Quora: design and evaluate experiments, build models and visualizations, analyze cross-product data to surface root causes, and partner with cross-functional teams to implement data-informed solutions and frameworks.

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.

As a Senior Data Scientist, you'll optimize search relevance, retrieve content, analyze data, and collaborate with teams to enhance product strategies.

The role involves deploying data science solutions in cybersecurity, collaborating with customers and teams to operationalize models and enhance security insights.

Lead data-driven strategy by partnering with senior executives to deliver rigorous analytical solutions. Design and implement sophisticated analyses on large-scale data, build trusted cross-functional relationships, mentor data scientists, and influence long-term product and business decisions.

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

Embedded on a core business team, own end-to-end analytics: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions across growth, product, AI, or partnerships.

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Design, validate, and deploy scalable statistical and distributional models for enterprise consumer analytics. Implement rigorous methodologies, convert ad-hoc analyses into version-controlled analytical libraries, and partner with Data Engineering to optimize performance and scale compute workloads (including cloud/Databricks). Deliver reproducible analytics powering dashboards and LLM-driven applications, with a focus on panel and transaction-level consumer data.

Design, build, and deploy predictive GTM models (LTV, attribution, propensity). Lead experimentation and causal analyses, define KPI measurement frameworks, partner with Data Engineering, and translate statistical insights into actionable recommendations for Sales, Marketing, and Customer Success.

Lead a 5–8 person Data Science team to develop and operationalize FWA detection models using SAS and Python on multi‑payer healthcare claims. Oversee model development, data pipelines, quality reviews, stakeholder presentations, and collaboration with SMEs and BI developers. Split role ~40% management, 60% hands-on coding/analysis.

As a Staff Data Scientist, you will lead initiatives to build and optimize machine learning models, collaborate across departments, and solve complex business problems using data.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.

As a Data Scientist, you will develop predictive models, analyze geoscientific data, and collaborate with geoscientists to improve mineral exploration efforts.

The Data Scientist II will oversee data management, design study protocols, train staff, lead report development, and manage client activities using project frameworks.

Partner with product engineering to design and analyze experiments, apply causal reasoning and statistical modeling to marketplace data, and drive data-informed product decisions across the engineering org.

Provide analytics and data-driven insights for CoverMyMeds clients, prioritize work that drives commercial outcomes, build relationships with account teams, apply statistical and predictive methods, monitor portfolio health, deliver client-facing visuals and recommendations, support complex requests and escalations, and inform strategic decisions across product, analytics, and operations.

Develop frameworks and tooling to estimate long-term impacts of product changes from short-term experiment outcomes. Build causal inference methods (experimental, econometric, quasi-experimental), evaluate heterogeneous treatment effects, own major estimation problems, and communicate results to technical and non-technical stakeholders to drive better long-term decisions.

The Sr. Football Data Scientist will build, deploy, and refine analytical models for football insights, managing large datasets and collaborating with teams for high-quality analytics solutions.