Top Data & Analytics Jobs

Analyze marketplace and product performance using SQL, support experiments and advertising-effectiveness studies, build reusable datasets, QA metrics, and document analytics. Collaborate with analytics engineers, data scientists, product managers, engineers, and commercial teams while developing skills in statistics, causal inference, Python/R, and marketing science.

Build and lead Apptronik’s People Analytics function, developing workforce analytics strategy, predictive models, dashboards, KPI frameworks, and data governance. Advise executive leadership on talent strategy, organizational health, workforce planning, and organizational design. Establish people-data standards, security, access controls, compliance practices, and architecture in partnership with IT and Data Engineering. Translate workforce data into actionable business narratives while mentoring analytics teams and supporting HR initiatives.

Leads the strategy, architecture, and deployment of AI-enabled business intelligence infrastructure. Designs governed semantic layers, data models, and BI systems using dbt and enterprise data warehouses. Manages and coaches a technical engineering team, partners with executives and cross-functional stakeholders, and ensures reliable, high-performing data pipelines, warehouses, and reporting tools. The role also advances AI-driven analytics, data discovery, and self-service reporting across the organization.

Analyze player behavior, product performance, revenue, retention, and engagement for Zynga Poker. Design experiments, dashboards, ETL pipelines, telemetry, fraud models, and business intelligence solutions. Partner with product, game design, economy, and consumer insights teams to guide decisions and improve player experiences. Contribute to AI-enabled analytics workflows, game integrity initiatives, and analytics best practices.

Own customer data migrations from legacy systems through QA and launch. Clean, map, import, and validate event, customer, order, donation, ticketing, and marketing data. Configure and troubleshoot integrations, APIs, webhooks, sync failures, and production data issues using SQL, logs, dashboards, and administrative tools. Create migration playbooks, documentation, validation processes, and rollback plans while partnering with customers, support, product, and engineering.

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.

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.

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.

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.