Top Hybrid Data Analysis Jobs

Lead and grow a marketplace growth analytics team to drive product and marketplace performance. Define success metrics, own experimentation strategy, deliver rigorous analyses (forecasting, causal inference, predictive modeling), partner with Product/Engineering/Finance, and translate insights into prioritized product decisions and reliable reporting. Balance strategic leadership with hands-on analytics and embed measurement into the product development lifecycle.

The role involves developing and maintaining risk models for quantitative risk management, collaborating with analysts and stakeholders, and enhancing model implementations.

10-week in-person internship partnering with Quant Researchers to explore research ideas, build analysis tools, learn options theory and market making, receive mentorship and professional development, and compete for a full-time Graduate Quant Researcher role.

Lead research strategy for Beauty, Style, and Entertainment verticals by analyzing large first-party datasets, synthesizing insights, advising marketing/editorial/sales, supporting RFPs and ad hoc requests, designing quantitative consumer research, and presenting findings to technical and non-technical stakeholders.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

The Senior Associate will analyze business needs, translate them into technical requirements, and collaborate with teams on enterprise-scale tech solutions, primarily in life insurance operations.

The Senior Data Scientist will lead analytics projects, define success metrics, run experiments, and present data-driven insights to influence product and business strategies.

The Senior Data Analyst for Payments will analyze and optimize payment processes, collaborate with cross-functional teams, and ensure regulatory compliance to improve financial operations.

Lead analytics strategy and decision support across Product, Growth, Revenue, Operations, and Finance. Perform deep-dive analyses, design experiments, build predictive models and ML/AI prototypes, create trusted reporting and dashboards, ensure data quality, automate workflows, and partner with stakeholders to drive measurable business outcomes. Act as a primary analytics partner, prioritize work, communicate recommendations, and mentor analysts informally.

Lead analytical work to monitor loan portfolio and originations, detect credit and underwriting issues, build multivariate statistical models, analyze funnels, quantify costs/benefits, present recommendations to executives, design monitoring and controls, and drive implementation using SQL, Python, Excel, AI tools, and financial/statistical techniques.