Top Analytics Jobs in NYC, NY

Develop and deploy analytical and AI-enabled tools integrated with the Aladdin platform to support portfolio construction, investment research, relative value analysis, risk budgeting, due diligence, and portfolio monitoring. Partner with portfolio managers and engineering teams to identify opportunities, prototype solutions, manage delivery, and productionize scalable applications. Communicate insights clearly while applying knowledge of financial markets, asset classes, Python, SQL, and modern technology stacks.

Leads complex business analyses for Engineering, building financial and operational models, datasets, metrics, dashboards, and executive decision materials. Identifies efficiency and cost-saving opportunities, designs resource-allocation frameworks, manages recurring planning and reporting, and coordinates cross-functional initiatives across Engineering, Product, Modeling, Finance, and Corporate teams.

Own product analytics strategy for a retail banking product, influencing roadmap and investment decisions through experimentation, causal inference, statistical modeling, and KPI frameworks. Query and transform large datasets using SQL, Python, or R; design and analyze A/B tests; identify growth opportunities; and communicate actionable insights to Product, Engineering, Finance, Research, and executive stakeholders.

Leads quantitative and qualitative Medicaid policy research from project scoping through dissemination. Oversees data acquisition and analysis, monitors state and federal policy changes, develops briefs and presentations, conducts stakeholder interviews, supervises research staff, manages external collaborators, and translates findings into actionable recommendations for policymakers, providers, advocates, and the public.

Executes quantitative analytics for cobrand credit card portfolios, focusing on acquisition, engagement, retention, attrition, rewards, and cardholder value. Develops analytical frameworks, supports experimental design, maintains data integrity, applies segmentation and generative AI, and presents actionable recommendations to senior leaders and partners. Collaborates with marketing, product, and analytics teams to improve partnership strategy and customer outcomes.

Own product analytics for embedded business areas, leading experimentation, root-cause analysis, business-case development, KPI reporting, and strategic recommendations. Build dashboards and Looker explores, partner with engineering teams to improve data models and reliability, present insights to leadership, use AI tools to improve analytics efficiency, and mentor analysts. The role requires advanced SQL, Python, statistical experimentation expertise, and experience with consumer fintech or similar B2C data.

Manage data analytics for PULSE Risk & Compliance by analyzing large datasets, identifying transaction anomalies and risk exposure, validating models, improving reporting and processes, and supporting compliant data strategies. The role involves Python-based programming, BI, database and data-storage design, strategic testing, cross-functional collaboration, project leadership, and people management in a hybrid environment.

Leads data analytics strategy, modeling, testing, reporting, and process improvements across business units. Mines complex databases, evaluates products and processes, improves operational efficiency, and consults on data systems. Manages and mentors junior analysts while supporting projects through the full lifecycle. The role emphasizes business intelligence, programming, strategic analysis, and collaboration in a fast-paced environment.

Analyze complex marketing and customer datasets to produce actionable insights, executive dashboards, recurring reports, and campaign performance analyses. Define metrics, evaluate trends, communicate findings to senior leaders, and partner cross-functionally to support growth and improve marketing outcomes. Independently manage analytical workstreams, optimize processes, and develop data products incorporating artificial intelligence and large language models.

Develop data models, queries, reports, and analytics for commerce enablement, controls, risk, and regulatory functions. Translate business needs into high-quality datasets and meaningful descriptive, diagnostic, predictive, and prescriptive insights. Partner with product, data management, strategy, technology, and analytics teams to define metrics, automate recurring reporting, rationalize complex data, and present findings to stakeholders for decision-making.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, experimentation, campaign reporting, retention analysis, churn modeling, segmentation, and LTV analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and deliver actionable recommendations. Requires strong SQL and Python skills, causal measurement expertise, marketing platform experience, and the ability to communicate insights to senior stakeholders.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Own the analytics lifecycle from complex raw data through executive-ready insights. Design experiments, analyze performance drivers, build scalable data pipelines and analytical frameworks, and communicate findings to marketing, product, and technology stakeholders. The role supports customer acquisition, owned media optimization, repeatable reporting, and roadmap decisions through secure, maintainable SQL and Python or R solutions.

Leads product analytics and partners with product and executive leadership to guide strategy, roadmap prioritization, experimentation, and optimization. Translates customer and business questions into measurable outcomes, analytical roadmaps, segmentation, funnel and cohort analyses, and evidence-based recommendations. Owns product measurement frameworks, dashboards, data quality, instrumentation, and governance while communicating insights, trade-offs, and actions to senior stakeholders.

The Senior Data Scientist will lead analytics projects, define success metrics, run experiments, and present data-driven insights to influence product and business strategies.

Leads analytics strategy across eCommerce, content, advertising, and live events. Partners with executives to turn ambiguous business questions and imperfect data into actionable recommendations, identifies business opportunities and risks, guides analytics priorities, and manages a team of three analysts. Requires strong SQL, Python or R, statistical reasoning, BI experience, AI-enabled workflows, and the ability to influence strategic decisions.

Analyze customer behavior, segmentation, clickstream data, attribution, and marketing campaign performance. Design A/B tests, apply statistical modeling using SQL, Python, and SAS, and develop automated Tableau dashboards and reporting. Provide actionable insights to improve customer acquisition, retention, engagement, and marketing ROI.

Analyze business performance and develop data-driven insights for the U.S. Small and Medium Enterprise business line. Use Python, SQL, data mining, and statistical modeling to define success metrics, track KPIs, identify growth opportunities, and optimize processes. Lead cross-functional projects from conception through rollout while partnering with Sales, Marketing, Product, Finance, and governance teams. Communicate findings, drive alignment, and support strategic and day-to-day business decisions.

Analyze complex banking and client datasets to identify trends, opportunities, and actionable insights. Partner with cross-functional teams, develop analytical frameworks and metrics, create executive-ready recommendations, improve analytics through automation, and ensure data quality. The role also mentors and oversees a junior team member while supporting strategic decisions for Morgan Stanley’s U.S. Banks.

Leads advanced Brand and Consumer analytics, integrating insights across marketing mix modeling, forecasting, commercial performance, and digital commerce. Develops data-driven narratives, translates complex analyses into actionable recommendations, and advises executives and stakeholders. Builds trusted client relationships across Marketing, IT, Sales, and Finance while using SQL, Python, statistical methods, and hypothesis-driven analysis to identify performance drivers and business opportunities.

Leads risk analytics projects and teams for property and casualty reinsurance. Oversees advanced statistical and machine learning model development, validation, deployment, and adoption in underwriting. Partners with data scientists, engineers, actuaries, underwriters, claims, legal, and external data providers. Generates analytical opportunities, supports pricing, communicates complex findings, and promotes innovation across the actuarial organization.

Own revenue forecasting models, pipeline analytics, and commercial performance insights across a global flexible-workspace network. The role integrates data from Salesforce, Looker, Snowflake, and spreadsheets; analyzes pricing, conversion, sales velocity, unit economics, and marketing and sales efficiency; partners with Finance and commercial leaders on budgets and planning; and communicates findings through actionable memos and presentations.

Leads the strategy, team development, and execution of GEICO’s performance marketing analytics function. Builds measurement frameworks, incrementality testing, anomaly detection, and marketing-spend optimization across search, SEO/AEO, programmatic, social, email, and direct mail. Partners with executives to translate analytics into decisions, establishes governance and quality standards, and applies AI and LLM-assisted workflows to improve insight generation and team effectiveness. Recruits and develops managers and channel specialists while aligning with broader data science, engineering, and business intelligence teams.

Leads retention analytics strategy for marketing, including causal measurement, holdout and test-control design, forecasting, scorecards, segmentation, business cases, and churn insights. Partners with senior marketing, Data Science, Business Intelligence, and Data Operations stakeholders to improve retention decisions. Builds automated reporting, establishes metric and quality standards, evaluates data and tools, and presents executive-ready recommendations. Requires hands-on analysis in renewal or subscription businesses and strong SQL, BI, and Python or R skills.

Own analytics for GEICO’s aggregator, vertical search, marketplace, and lead-generation partners. Build scorecards, analyze quote-to-purchase funnels, measure incrementality, evaluate bidding and partner economics, monitor data integrity, and recommend investment and negotiation strategies. Partner with marketing, finance, business intelligence, and external partners to automate reporting, improve tracking, forecast performance, and influence senior leadership decisions.