Top Data & Analytics Jobs

Conduct rigorous research using statistics and machine learning to extract patterns from datasets. Implement algorithms, back-test models, and document findings.

The Director of Business Development will define, negotiate, and secure partnerships to expand adMarketplace's search and performance advertising across various platforms while ensuring alignment with company goals and operational integration.

Design and build scalable analytic tools and systems to improve localization quality and efficiency. Partner with engineers, scientists, and product teams to improve data models, productize insights, and drive localization strategy. Act as an LA ambassador for the Globalization Data Science and Engineering team.

Lead a team to analyze, optimize, and grow merchant revenue using analytics and AI. Define strategy, set KPIs, deploy ML solutions, drive go-to-market alignment, execute tests, and deliver actionable insights to executives and cross-functional partners.

Lead partner analytics by building scalable dashboards, forecasting and ROI models, and experimental designs to evaluate and optimize partner performance. Collaborate with Product, BD, Marketing, and Data Engineering to improve pipelines, translate insights into recommendations, and mentor analysts to scale partner growth.

Work within Morgan Stanley's Business Solutions Group to deliver consulting engagements, program delivery, and data-driven analytics. Manage cross-functional projects, define problems, design data platforms, build dashboards and automation, analyze financial and operational data, and support ML/LLM initiatives including RAG and agentic workflows. Engage stakeholders, track risks and metrics, and prepare presentations for senior management.

The Data Scientist/Manager will analyze data, develop models, support organizational missions, and provide insights to enhance decision-making for the USDA.

Lead a team in delivering data-driven insights for underwriting and risk selection, managing projects and fostering relationships across business units.

The Director leads global HR analytics, driving innovation and delivering data-driven strategies to enhance colleague experiences, operational excellence, and decision-making through advanced analytics and automation.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

The Senior Manager of Sales Insights and Analytics leads the transformation of data into actionable insights, enhancing sales performance through strategic analytics and stakeholder collaboration.

Lead automation of billing, journal entries, reconciliations, and recurring accounting reports. Design and maintain workflows connecting Accounting with other teams, analyze accounting data, build dashboards, and apply ML for forecasting and anomaly detection. Partner with IT and Accounting leadership, document controls, train staff, and drive automation projects from identification through implementation.

Partner with Supply Chain functions to design and deliver digital process improvements and analytics solutions (dashboards, automation, low-code apps, ML/AI). Own end-to-end delivery from intake, backlog prioritization, and data prep to deployment, adoption, and value realization while driving change management and reusable team practices.

TigerGraph seeks individuals to promote their scalable graph database technology used for analytics and machine learning across various industries.

Manage end-to-end catastrophe modeling projects, support client discussions on reinsurance strategy and portfolio management, maintain stakeholder relationships, develop region/peril expertise, perform data management and technical analysis, and lead internal research and automation initiatives.

Design, develop, maintain, and execute complex financial models for loss forecasting, stress testing, pricing, originations/collections, and portfolio optimization. Use Python or R (and SQL/SAS/other languages) for data processing and model development, build Power BI analytics, collaborate with business partners and regulators, support model validation/audits, research industry/academic methods, and develop data environments to support quantitative activities.

Design and implement scalable analytics/data models and dbt pipelines, manage Databricks, build dashboards and BI solutions, partner with business stakeholders, support CRM/marketing analytics, and explore GenAI/ML opportunities to deliver reliable, automated data products.

Lead data-driven initiatives by partnering with marketing, product, and BD to inform acquisition and partnership strategies. Design, run, and analyze A/B experiments, leverage machine learning for in-depth analyses, test growth levers, and automate manual processes to improve operational efficiency.

Support business growth by driving data-driven decisions: run analyses, design and analyze A/B tests, define acquisition levers, partner cross-functionally, and automate operational processes.

Partner with cross-functional teams to drive data-driven growth: design and analyze A/B tests, leverage machine learning for insights, define acquisition and partnership levers, and automate processes to improve operational efficiency.

Partner with marketing, product, and biz-dev to drive data-driven growth. Design, run, and analyze A/B tests, define acquisition and partnership levers, leverage machine learning for insights, and automate operational processes to improve efficiency and scalability.

Design, build, and maintain large-scale data infrastructure and pipelines (data lakes/warehouses). Integrate diverse data sources, optimize processing and queries, enforce data quality and security, implement monitoring/alerting, troubleshoot issues, and collaborate with cross-functional teams while exploring new data frameworks and cloud services.

Support data collection, cleaning, and analysis using Power Platform or scripting. Build and validate data models, assist with predictive analytics/ML, monitor solution performance, and communicate findings to team members and clients.

Participate in a multi-week training then rotate across analytics teams (quantitative modeling, model risk, market risk, fraud, commercial analytics, client/employee experience, credit portfolio). Perform data analysis, develop predictive models, produce reports and visualizations, communicate insights to senior stakeholders, conduct market research, and support financial and regulatory reporting.

Lead a quantitative modeling team to develop and govern credit underwriting, pricing, collections, and portfolio risk models. Collaborate with stakeholders on acquisition pricing, marketing optimization, M&A risk assessment, and model validation. Oversee model performance, governance, and implementation to support lending strategies and maximize profitability while minimizing credit losses.