Top Data & Analytics Jobs

The Senior Data Scientist will develop optimization models, manage the model lifecycle, and collaborate across teams to enhance Lyft's marketplace efficiency and strategy.

Designs, builds, and maintains scalable ETL pipelines and databases; integrates large-scale data for analytics; develops and tests code, queries, and reports; ensures data quality and governance; leads solution development, trains users, and supports ML and BI initiatives.

Design and execute advanced inferential and predictive analyses and study designs for population and behavioral research. Support survey weighting, variance adjustments, sample blending, data preparation and quality monitoring. Contribute to technical deliverables, literature reviews, causal inference and synthetic data solutioning, visualizations, and stakeholder communication while collaborating with interdisciplinary teams and HPC engineers.

Design and conduct rigorous people research (experiments, longitudinal studies, psychometrics) to measure employee experience, manager effectiveness, and organizational health. Build surveys, analyze data with SQL/Python/R, create visualizations and dashboards, translate findings into recommendations, and partner with People stakeholders to inform people strategy.

Design and implement scalable data pipelines in Databricks/AWS, develop and optimize ELT/ETL workflows from warehouses, lakes, APIs and financial systems, and build/train/deploy/monitor ML and generative AI models. Support BI tooling (Excel, Python, Tableau, SharePoint), train team members, assist project QA and client engagement, and translate stakeholder requirements into actionable reports.

Lead and manage global teams delivering commercial analytics and technology initiatives for Life Sciences, while driving projects related to field force design and sales effectiveness.

As an Engineering Manager, you'll lead efforts to enhance model performance, manage team projects, and support professional growth in a dynamic environment.

The Quantitative Research Analyst will develop execution strategies, conduct market research, and analyze execution costs for Futures and FX trading.

The Head of Data will shape the data architecture, manage data infrastructure, and facilitate insights through self-serve analytics while collaborating with AI teams.

The Business Strategy Optimization Analyst utilizes analytical techniques to drive profitability, influence strategy, and improve customer experiences through data analysis and modeling.

The role involves leading data science initiatives, managing large datasets, developing predictive models, and building a high-performing analytics team.

Join Chevron as an intern in Information Technology – Information and Analytics. Interns will apply data science and analytics to support sustainable energy initiatives. Responsibilities include data analysis, modeling, and contributing to data-driven decision-making processes across multiple areas.

The Data Analyst will conduct full lifecycle analysis, develop reporting capabilities, monitor performance, and identify improvements in data quality and efficiency.

Lead digital marketing measurement and data science, analyze digital data, develop statistical models, and collaborate with marketing teams for optimization and insights.

The Director will lead InMobi's strategy for data, identity, and audience ecosystems, overseeing partnerships and ensuring compliance while driving business outcomes.

The Data & Analytics team at Surescripts transforms healthcare data into actionable insights, collaborating with various stakeholders to support critical decisions across the healthcare ecosystem.

As a Data & Analytics Analyst, you'll collaborate with clients to create tailored solutions, implement prototypes, and share ideas to solve analytical challenges.

The Quantitative Researcher will focus on creating predictive alpha signals, applying ML techniques, and optimizing execution in cash equities. Close collaboration with teams to maximize P&L opportunities is key.

Lead North America marketing analytics product portfolio, evolve MMM to causal and AI-native methods, prioritize roadmap and epics, oversee data engineers and scientists, drive adoption and value measurement for marketing effectiveness.

Lead development and implementation of analytics and measurement frameworks for marketing campaigns. Advise clients on test design, KPI assignment, attribution, and optimization. Connect multiple data sources, generate actionable insights, build visualizations and automated reporting, mentor analysts, and drive analytics innovation to improve media and omni-channel performance and ROI.

Lead financial system implementations and integrations, configure financials for new properties, ensure accurate operational-to-financial data flows, drive process automation and data governance, partner with Accounting and IT, manage vendor relationships, and support reporting and change management.

Lead and coordinate RA work to ingest, clean, transform, and analyze economic and financial datasets; apply ML (including tree-based and boosted time-series/panel models) and NLP; build data visualizations (PowerBI) and presentations; contribute to design and estimation of risk-assessment models.

Design, implement, and maintain scalable data pipelines and platforms for structured and unstructured data to support AI/ML workloads. Ensure data governance, security, monitoring, and CI/CD for ETL workflows across on‑prem, cloud, or hybrid environments while collaborating with cross‑functional technical teams.

Design, build and maintain a self-service data platform to enable teams to create data products. Support real-time analytics, batch processing and ML workloads. Implement secure, scalable, compliant infrastructure with IaC and automation. Enable ingestion, processing and consumption of data at scale. Mentor teammates and drive engineering excellence.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.