Senior Data Analyst - Alternative Data & Retail

YipitData is the leading market research and analytics firm for the disruptive economy, backed by a $475M investment from The Carlyle Group at a $1B+ valuation. Every day, YipitData processes billions of alternative data points to deliver market intelligence to top investment funds and Fortune 500 enterprise brands like Uber, 3M, and Summer Fridays.

As the Senior Data Analyst / Emerging Sectors Data Lead, you will take full technical and strategic ownership of introducing and scaling YipitData's consumer data offerings into entirely new industry verticals. Reporting to the Head of Data, you will operate as a "player-coach"—combining hands-on data transformation using SQL, Python, PySpark, and Databricks with mentorship, workflow design, sector taxonomy development, and cross-functional leadership across Data, Insights, Revenue, and Engineering teams.

Key Responsibilities

• Emerging Sectors Data Strategy: Own data strategy, accuracy, and pipeline execution for new corporate sector deliverables, driving product adoption, client confidence, and ARR growth.
• Data Transformation & Pipelining: Transform large, complex, and unrefined consumer transaction datasets into clean, reliable, production-grade metrics using SQL, Python, PySpark, GitHub, and Databricks.
• Taxonomy & Categorization Ownership: Build, maintain, and continuously evolve core sector classification frameworks, product attribution models, and custom client taxonomies.
• Client & GTM Subject Matter Expertise: Serve as the technical SME for emerging sector data, partnering with Go-To-Market (GTM) teams in client discussions to explain methodology, data lineage, and quality standards.
• Data Quality & Incident Resolution: Proactively audit, troubleshoot, and resolve complex data quality issues, engineering automated and scalable validation checks to prevent future defects.
• Player-Coach Leadership: Set high standards for execution speed and analytical rigor while coaching and mentoring junior and mid-level data analysts on your team.

Requirements

Practical Experience & Technical Skills

• 8+ years of professional experience in data analytics, data operations, or data-driven management consulting.
• 2+ years in a technical lead, manager, or player-coach capacity.
• 4+ years of hands-on experience using SQL, Python, PySpark, or similar languages to wrangle, clean, and model large, complex, and evolving datasets.
• Demonstrated experience handling unstructured or messy data, with a strong background in taxonomy design, category classification, and data normalization.
• Familiarity building and maintaining production data workflows in environments like Databricks, Spark, and GitHub.

Soft Skills & Work Logistics

• Strong ownership mindset with a proven ability to bring structure to fast-paced, ambiguous environments.
• Excellent technical communication skills with a track record of bridging technical details with non-technical business partners and enterprise clients.
• Must reside in the United States and be authorized to work without present or future visa sponsorship.

Preferred Qualifications

• Experience working with consumer transaction data, e-commerce data, alternative datasets, or retail market research.
• Hands-on experience collaborating closely with Go-To-Market, Revenue, and Product Management leadership to shape commercial strategy.

Total Rewards & Benefits

• Compensation & Equity: On-target base salary of $170,000 – $190,000 USD + 10% annual variable bonus target + equity ownership package.
• Health & Personal Life: Comprehensive medical, dental, and vision insurance options; generous 401(k) employer matching program.
• Flexibility & PTO: Flexible remote work culture, flexible vacation policy, paid parental leave, learning reimbursements, and annual wellness budgets.