Note: The job is a remote job and is open to candidates in USA. YipitData is hiring a Senior Data Analyst for its Data Feeds team, which turns proprietary datasets into commercial data products for institutional investors. The analyst will own and improve data products, evaluate data and methodologies, and work cross-functionally to translate customer needs into product enhancements and new analytical capabilities.
Responsibilities
- Own commercial data products – Own products end-to-end, from methodology development and product QA to feature design and ongoing product evolution. Develop deep expertise in how your product works and the investment workflows it supports
- Improve product quality through systems – Investigate complex data quality issues spanning upstream datasets, product methodologies, and downstream customer outputs. Build scalable monitoring, validation, and QA frameworks that improve quality while reducing manual effort
- Shape the evolution of the product – Work with Product Managers, Data Science, and Central Data. Identify opportunities for new methodologies, additional datasets, forecasting capabilities, AI-powered features, and entirely new product offerings
- Evaluate new data and methodologies – Analyze new internal and third-party datasets to determine whether they improve product accuracy, coverage, or customer value. Design experiments, quantify tradeoffs, and help determine what belongs in production
- Turn customer feedback into better products - Partner with Product Managers, Client Strategy and directly with sophisticated investors to understand how products are being used. Translate customer questions, trial feedback, and support escalations into durable product improvements
- Use AI to redesign analytical workflows – Leverage AI agents, automation, and evaluation frameworks to improve QA, documentation, methodology development, and customer-facing analytical experiences
- Build the next generation of data products – Look beyond maintaining today's products. Identify opportunities to create new analytical capabilities, improve client workflows, and expand the ways customers interact with our data
Skills
- You have 4+ years of experience in data analytics, with a background in financial services, consulting, data science, product analytics, or another environment where complex data informs high-stakes decisions
- You have advanced SQL skills and experience using Python or PySpark to build reliable, reusable analytical workflows
- You enjoy building products—not just analyzing data—and naturally think about how information should be packaged, delivered, and experienced by customers
- You quickly develop strong mental models for complex datasets and enjoy reasoning through ambiguity to identify root causes and improve methodologies
- You have led complex cross-functional projects involving Product, Engineering, or analytical stakeholders and are comfortable driving work from idea to execution
- You know how to balance rigor with pragmatism, making thoughtful tradeoffs between speed, quality, and long-term product value
- You're skilled at working with messy, evolving datasets and enjoy creating structure, repeatability, and confidence in complex systems
- You communicate technical concepts clearly and can explain methodologies, assumptions, and tradeoffs to both technical teammates and business stakeholders
- You actively use AI tools and are excited about fundamentally changing how analytical products are built—not just making existing workflows more efficient
- We are not able to consider candidates who currently or in the future will require visa sponsorship
Benefits
- Flexible work hours
- Flexible vacation
- A generous 401K match
- Parental leave
- Team events
- Wellness budget
- Learning reimbursement
- Fully remote work within the United States
Company Overview