[Hiring] Senior Data Analyst @YipitData (Alternative)

Role Description

YipitData's Data Feeds team transforms our proprietary datasets into commercial data products used by many of the world's largest hedge funds, asset managers, and quantitative investors. Our products help investors answer questions about consumer spending, enterprise software adoption, cloud infrastructure, healthcare, and dozens of other markets—using proprietary datasets that clients integrate directly into their investment workflows.

The Data Feeds team creates products that fit seamlessly into client investment workflows—whether that's through granular datasets, aggregated metrics, forecasting methodologies, APIs, or entirely new AI-powered product experiences.

As an analyst on the team, you'll sit at the intersection of analytics, product, and commercialization. You'll partner closely with:

• Product Managers
• Central Data
• Data Science
• Engineering
• Quant Research
• Client Strategy

We're hiring across multiple products, including:

• Kepler — consumer transaction datasets powering institutional investment workflows through granular transaction data, aggregated metrics, and forecasting products.
• Summit — B2B spend datasets built from purchase and invoice data, helping investors understand enterprise software, industrials, healthcare, and other sectors.
• Edison – email receipt datasets built from one of the industry's largest anonymized inbox panels, helping investors track consumer purchases, subscriptions, travel, and digital commerce across thousands of merchants.
• SpendHound – Proprietary B2B software spend datasets built from ERP, expense, and invoice data, helping investors understand software adoption, customer retention, competitive dynamics, and enterprise technology spending.
• Cloud – Enterprise cloud infrastructure data covering AWS, Azure, Google Cloud, and Oracle Cloud, combining proprietary spend panels with pricing and capacity data to help investors understand cloud growth, AI infrastructure demand, and competitive dynamics.

This role is different from a traditional Data Analyst position. Success isn't measured by how many analyses you complete. It's measured by the quality of the products you build, the customer problems you solve, and the leverage you create for clients and the business.

We’re open to hiring this role at multiple levels. While the position is posted as Senior Data Analyst, we encourage applications from candidates with a range of experience who can demonstrate strong analytical judgment, ownership, and growth potential. Final title, scope, and compensation will be calibrated based on experience and demonstrated skills.

As an analyst on the Data Feeds team, you will:

• 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.

Over your first year, you might:

• Design a new aggregation methodology that significantly improves the accuracy of a commercial transaction product.
• Evaluate a new third-party dataset and determine whether it should become part of a production product.
• Build automated QA monitors that proactively detect regressions before customers notice them.
• Partner with Data Science to evaluate the impact of model improvements on customer-facing metrics.
• Create an AI-powered workflow that dramatically reduces the time required to investigate complex customer-reported data issues.
• Launch a new forecasting capability or AI-powered analytical feature that expands how clients use our products.

Qualifications

• 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.
• Advanced SQL skills and experience using Python or PySpark to build reliable, reusable analytical workflows.
• Enjoy building products—not just analyzing data—and naturally think about how information should be packaged, delivered, and experienced by customers.
• Quickly develop strong mental models for complex datasets and enjoy reasoning through ambiguity to identify root causes and improve methodologies.
• Led complex cross-functional projects involving Product, Engineering, or analytical stakeholders and are comfortable driving work from idea to execution.
• Know how to balance rigor with pragmatism, making thoughtful tradeoffs between speed, quality, and long-term product value.
• Skilled at working with messy, evolving datasets and enjoy creating structure, repeatability, and confidence in complex systems.
• Communicate technical concepts clearly and can explain methodologies, assumptions, and tradeoffs to both technical teammates and business stakeholders.
• Actively use AI tools and are excited about fundamentally changing how analytical products are built—not just making existing workflows more efficient.

Benefits

• Flexible work hours
• Flexible vacation
• Generous 401K match
• Parental leave
• Team events
• Wellness budget
• Learning reimbursement

The annual base compensation for this position is anticipated to be $140K–$190K, reflecting the range of levels at which we may hire. Final title, scope, and compensation will be determined based on the candidate’s experience, knowledge, skills, abilities, and internal team benchmarks.

The total compensation package includes a mix of base, bonus, equity, and benefits.

This role may be performed fully remotely within the United States. Please note that our US headquarters are located in NYC. If the remote work is performed outside of these offices, income may be subject to New York State tax withholding.

Please note that for this position, we are not able to consider candidates who currently or in the future will require visa sponsorship.

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity employer.