Top Data & Analytics Jobs

Build data pipelines and relational data models using Python and SQL; clean operational data, support scenario analysis, and create dashboards for PMO leadership. Explore LLMs and machine learning for text analysis and data-quality automation. Gain production experience with testing, documentation, maintainable code, and data-driven decision support in a trading environment.

Develops fraud rules, models, dashboards, and strategies to reduce fraud losses. Analyzes emerging fraud trends, monitors KPIs, conducts ad hoc analysis, supports production deployments, and communicates findings to technical and business stakeholders. The Thursday-through-Monday schedule requires weekend availability, with a hybrid arrangement based in Chicago.

Leads Apollo’s core data engineering organization, including Native Data, waterfall enrichment, and scraping platforms. Owns strategy, architecture, team growth, data acquisition, enrichment, synchronization, quality, freshness, monitoring, and large-scale ETL systems. Partners with executives and cross-functional teams to improve data coverage and reliability, establish feedback loops, select vendors, and apply AI to data acquisition and maintenance.

Lead Notion’s Data Foundations team by setting multi-quarter platform strategy, developing engineers and technical leaders, and guiding complex initiatives across data lakes, streaming, distributed compute, governance, and reliability. Drive enterprise-ready capabilities including data residency, access controls, lifecycle management, and key management. Improve Kafka, Debezium, S3/Iceberg, Spark, EMR, and Athena scalability, reliability, usability, and cost efficiency while partnering across engineering, AI, search, infrastructure, and security teams.

Build and operate reliable data systems and products supporting clinical operations, drug evaluation, business development, analytics, machine learning, and AI agents. Responsibilities include designing pipelines, canonical data models, data contracts, warehouse transformations, quality and observability practices, governance for regulated data, and incident response. The role partners closely with Product Engineering and Data Science, uses AI-assisted development, contributes to architecture, and mentors other engineers.

Leads a team of data analysts focused on experimentation, KPI measurement, reporting, and optimization of banking and consumer engagement operations. Owns analytics strategy, A/B testing, automation measurement, Snowflake-based analytical solutions, dashboards, and self-service reporting. Partners with Operations, Product, Engineering, and Finance to drive strategic decisions, profitability, and efficiency. Coaches team members, supports hiring, applies AI tools to analytics workflows, and communicates recommendations to senior leaders.

Conduct quantitative research to design, implement, and deploy mathematical trading models. Build custom tools for exploratory analysis, apply rigorous quantitative techniques to solve complex problems, and collaborate with traders and developers to productionize models while maintaining best practices.

Build and maintain enterprise Workday reporting solutions, dashboards, calculated fields, and automated reporting processes across HR and finance functions. Advise HR stakeholders, ensure data quality and governance, support compliance, document reporting logic, manage releases and rollouts, troubleshoot production issues, and mentor junior team members.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Develops Tableau dashboards, writes optimized SQL, and supports analytics initiatives using large datasets. The intern collaborates with business and technical teams to gather requirements, troubleshoot data issues, and improve access to internal data. Responsibilities include contributing to data warehouse design, maintaining ETL processes, coding, testing, debugging, documentation, and using AI-assisted development tools such as Claude Code. The role operates in a regulated, agile environment and supports data-driven decision-making.