Top Data & Analytics Jobs

Owns analytics and optimization strategy for advertising revenue across Zynga’s mobile game portfolio. Responsibilities include monitoring performance, diagnosing trends, designing A/B tests, identifying monetization opportunities, partnering with product, analytics, and data science teams, supporting AI and ML models, leading cross-functional initiatives, and mentoring analysts.

Conduct quantitative research and post-trade analytics for securities lending. Develop trading signals, models, algorithms, and automated workflows; own production model monitoring and governance; apply AI and machine learning; and collaborate with traders, researchers, technologists, investors, and risk managers to deliver scalable electronic trading solutions.

Translates business problems into analytical designs, performs quantitative analysis, and delivers data-driven recommendations. Uses disparate enterprise data sources, predictive analytics, visualization tools, and automation to support business decisions. Leads analytics projects, communicates insights to stakeholders, mentors analysts, measures business impact, and partners with development teams on tracking solutions and integrations.

Leads technology, data, automation, analytics, and applied AI solutions supporting investment manager research across public and private markets. Translates business requirements into scalable production systems, develops applications and dashboards, improves data quality and governance, and prototypes AI/LLM capabilities. Partners with research, investment, data, technology, operations, and vendor stakeholders while managing complex initiatives, controls, priorities, and adoption.

Manage deposit-account fraud losses through advanced analytics, reporting, data mining, and machine learning. Identify fraud trends and mitigation opportunities, improve predictive models, develop dashboards, communicate insights to leadership, and support technical projects. Collaborate with banking, risk, operations, IT, vendors, and consultants while mentoring teams and driving analytical best practices.

Conduct quantitative research for automated trading strategies by developing mathematical models, translating algorithms into code, backtesting trading signals, analyzing unconventional data, and refining monetization systems. Collaborate with senior researchers during an 11-week post-doctoral internship while applying advanced probability, statistics, machine learning, and time-series techniques to financial markets.

Leads enterprise competitive intelligence capabilities, including data collection, matching, scraping, governance, quality standards, analytical methodologies, and AI-enabled workflows. Partners with Product, Engineering, Data Science, Merchandising, Pricing, Digital, Marketplace, and Strategy teams to translate business needs into scalable solutions. Develops metrics, models, validation processes, and insights that support business decisions, while potentially managing and developing a small analytics team.

This internship develops quantitative analytics and financial engineering solutions for BlackRock’s Aladdin platform. Responsibilities include building financial risk models, applying quantitative techniques to investment and client-business problems, developing Python-based solutions, delivering actionable analytics, and collaborating with investment and business teams. Interns gain experience in financial markets, investment products, quantitative research, technology, and the Aladdin platform.

Participate in BlackRock’s quantitative investing internship across quantitative research, portfolio management, product strategy, and investment technology. Apply statistical models, machine learning, Python programming, and large-scale data analysis to investment strategies across asset classes. Learn about capital markets, portfolio trading, economic theory, client objectives, and investment product development while collaborating with research, technology, strategy, and investment professionals.

Provides analytics and strategic advisory support for mergers, acquisitions, and other business transactions. Analyzes contract data to identify risks, obligations, performance insights, and compliance indicators; develops algorithms, data models, pipelines, dashboards, and predictive models using Python and machine learning. Collaborates with clients and internal teams, validates data integrity and security, mentors junior staff, and delivers data-driven recommendations.

Supports project planning and senior leadership through predictive modeling, historical data management, Power BI dashboards, automated Excel workbooks, data warehouses, forecasting, and enterprise reporting. Coordinates with Finance, Contracts, Project Management, and shipyard stakeholders to develop workflows, analyze schedule and cost performance, prepare ad hoc reports, and brief project findings. The role also applies AI and machine learning to data engineering, analytics, visualization, and predictive modeling.

Leverage advanced analytics, data manipulation, visualization, statistical modeling, predictive analytics, and machine learning to generate client insights and recommendations. Apply Adobe Experience Cloud solutions to support business transformation and strategic decision-making. Build client relationships, manage and inspire teams, navigate complex engagements, uphold professional standards, and deliver quality outcomes while developing technical and consulting expertise.

Leads data analysis and advanced analytics workstreams for clients, using statistical modeling, machine learning, data visualization, and Adobe Experience Cloud technologies to improve operations and strategic decision-making. Manages project planning, budgeting, execution, and completion while mentoring teams, maintaining data integrity and security, building Tableau and Power BI dashboards, identifying business opportunities, and integrating innovative analytics practices.

Leads data analytics projects that generate insights for strategic decision-making. Develops visualization solutions with Power BI and Tableau, builds data pipelines, applies statistical modeling and predictive analytics, and manages data integrity and security. Collaborates with clients on tailored data solutions while coaching analytical teams, managing accounts, overseeing project success, and identifying business opportunities.

Lead Data Engineer responsible for designing, developing, testing, implementing, and supporting cloud-based data and full-stack solutions. The role uses Java, Scala, Python, databases, distributed computing, streaming technologies, and cloud data warehouses. Responsibilities include collaborating across Agile teams, developing scalable solutions, conducting unit tests and code reviews, optimizing performance, keeping current with emerging technologies, and mentoring engineers.

Leads global customer experience analytics strategy, developing analytical frameworks, predictive models, KPI systems, dashboards, forecasting, segmentation, retention analysis, and operational insights. Partners with CX, contact center, product, data, and business leaders to improve satisfaction, efficiency, retention, and business outcomes. Manages analytics initiatives and teams while translating complex data into executive-level recommendations and narratives.

Designs and governs enterprise data architecture for on-premises warehouses, Hadoop, lakehouse, and graph environments. Leads data movement controls, reconciliation, orchestration, catalog governance, query federation, lineage, security, and auditability. Partners with business and technology leaders on requirements, roadmaps, design approvals, proofs of concept, compliance, and modernization. Requires expertise in data modeling, ETL/ELT, distributed systems, Hadoop, data warehousing, and enterprise architecture.

Design and build maintainable data pipelines, ETL processes, and data architecture standards. Collaborate with product managers, analysts, and machine learning engineers to translate requirements into automated, scalable solutions. Apply software engineering best practices, asynchronous systems, APIs, streaming, testing, monitoring, and Python and SQL expertise. Help prioritize data initiatives based on business impact and communicate complex technical concepts to technical and non-technical stakeholders.

Leads ad hoc and exploratory analyses for medical and business questions across a global Medical Insights organization. Prepares and validates datasets, translates ambiguous stakeholder needs into decision-ready findings, and maintains analytical documentation. Tests new data sources, methods, and AI-enabled approaches through proof-of-concept analyses to guide platform investments and roadmap decisions. Partners with business and product stakeholders while supporting compliant, reproducible use of regulated data.

Lead design and implementation of enterprise fraud prevention strategy and decisioning engines for loan products. Use data analytics and machine learning to assess fraud and identity risk, recommend verification standards, set KPIs, report to senior leadership, and lead/mentor a team to automate and improve fraud prevention while maintaining a frictionless customer experience.

Analyzes manufacturing, process, quality, and yield data to identify trends, anomalies, and improvement opportunities. Develops dashboards, visualizations, automated reports, statistical models, and machine learning solutions to investigate yield loss and process variation. Collaborates with engineering and manufacturing teams on process optimization and completes an end-to-end analytics project delivering measurable improvements in yield, cycle time, reporting, or decision support.

Paid, full-time 11-week summer internship for a rising senior pursuing a bachelor’s degree. The intern will analyze customer reliability issues, research escalations, manage resolution through compliance checks and internal coordination, and identify trends using data and AI/ML research methods. The program also includes mentorship, networking, professional development, community service, and cross-functional projects.

Paid, full-time summer intern supporting enterprise database environments across on-premises and cloud platforms. Responsibilities include assisting with Oracle, SQL Server, and NoSQL administration; database provisioning, patching, migrations, tuning, troubleshooting, security compliance, and audit support. The intern will also gain exposure to AWS Redshift, data warehouses, cloud operations, scripting, monitoring, automation, APIs, dashboards, and machine learning while collaborating with engineering and analytics teams.

Lead advanced risk, fraud, and payment optimization analyses for major fintech merchants. Analyze large-scale transactional, ML output, and labeled risk data; design experiments and statistical investigations; develop scalable analytical tools, ETL workflows, dashboards, and reusable frameworks; collaborate with risk product teams; translate findings into merchant strategies and product improvements; enable commercial stakeholders through playbooks and self-service tools; and mentor analysts.

Leads the Managed Services analytics roadmap, KPI governance, Power BI dashboard strategy, reporting automation, and AI-augmented metrics services on InterSystems IRIS. Provides technical leadership in SQL, ObjectScript, APIs, data models, interoperability, query optimization, and application performance. Establishes data-quality and reporting standards, develops predictive analytics, mentors analysts and engineers, investigates complex issues, and advises senior leadership on operational performance, risks, and investment priorities.