Top Remote Senior Data Science Jobs in NYC, NY

Leads AI and data consulting workstreams focused on fraud detection, payment integrity, and machine learning. Designs and deploys scalable analytics solutions, develops fraud rules and models, partners with clients on AI use cases, presents executive deliverables, mentors consultants, and ensures governance, security, and responsible AI alignment.

Build LLM-powered research and analysis products for political strategists. Partner with users to shape workflows, define quality standards, design evaluations and LLM-as-judge systems, prototype features, and communicate technical tradeoffs to technical and nontechnical stakeholders. The role requires strong Python, SQL, statistical and machine learning skills, hands-on LLM and embedding experience, product judgment, and comfort with ambiguous problems.

Own the analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; surface insights; and drive data-informed decisions with cross-functional stakeholders. The role requires independent analytical problem-solving, SQL or Python proficiency, strong communication, and ownership of ambiguous initiatives through measurable business impact.

Own end-to-end data science for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; and drive recommendations and decisions with cross-functional stakeholders. The role requires independent data work, strong analytical thinking, clear communication, and ownership of ambiguous problems that deliver measurable business impact.

Lead client engagements using data science, AI, advanced analytics, statistical modeling, experimentation, and marketing measurement. Manage and develop analysts and data scientists, advise quantitative researchers, pitch projects, grow client relationships, and provide thought leadership on machine learning and emerging AI methods. Translate technical work into strategic recommendations for clients and executives.

Designs and deploys advanced AI and machine learning solutions, including AI agents, RAG systems, analytical models, and data products on Google Cloud Platform. Responsibilities include preparing structured and unstructured data, developing AI agent tools, applying NLP and deep learning, collaborating with customers and stakeholders, generating business insights, and communicating analytical results.

Lead Fraud Data Scientist to define ML strategy, build and productionize fraud detection models (supervised and unsupervised), investigate emerging fraud patterns, run experiments, collaborate with Product/Engineering/Risk, and maintain dashboards tracking fraud KPIs.

Build and own the finance reporting layer in the data warehouse, reconcile ledger and platform transactions, produce production-ready financial reports, analyze fee and promotion impacts on revenue and retention, support monthly close and forecasts, and document models and reports end-to-end.

Own the member-facing mobile (and near-term signed-in web) product roadmap for AI-powered genomic experiences. Drive activation, engagement, retention, and trust by translating intelligence-layer capabilities into polished consumer UX, rapid prototypes, experiments, and clear PRDs while partnering with AI platform, engineering, bioinformatics, design, and customer success.

Develop foundation models for longitudinal wearable and physiological data, leading research from hypothesis development through modeling, experimentation, evaluation, prototyping, and product deployment. Build datasets and ML infrastructure, advance representation learning, forecasting, personalization, multimodal and generative modeling, and establish robust evaluation methods. Collaborate with scientists, clinicians, engineers, and product teams while translating research into health experiences.