Data Lead - Central Data Team

Eligible Region: USA · Workplace: 🌐 Remote

YipitData is the leading market research and analytics firm for the disruptive economy. Our proprietary technology analyzes billions of alternative data points to uncover actionable insights. The world's top investment funds and Fortune 500 companies depend on our data to drive high-stakes decisions.

We operate globally with offices in the US, APAC, and India. Our award-winning, people-centric culture - recognized by Inc. as a Best Workplace for three consecutive years - emphasizes transparency, ownership, and continuous mastery.

Ownershipis real, not aspirational. An analyst here can own a data product end-to-end - from methodology to client delivery - and present directly to the investors who depend on it. You won't spend months waiting for "meaningful work."

YipitData's Central Data team sits at the foundation of everything we deliver. We build the standardized data products, methodologies, and systems that power every downstream business — from our investment research and corporate products to our data feeds.

Historically, many teams solved similar data problems independently. Central Data exists to identify those common patterns and build shared solutions that improve quality, consistency, and speed across the company.

As a Central Data Lead, you'll own one of these foundational data domains end-to-end. This is a highly analytical product ownership role that combines deep data expertise, systems thinking, technical leadership, and cross-functional execution. Rather than solving one-off analytical problems, you'll design the reusable systems and methodologies that enable dozens of downstream teams to move faster with greater confidence.

Each domain is jointly led by a three-person leadership team:

Data Lead: owns methodology, data quality, and analytical strategy

Technical Product Manager: owns prioritization, roadmap, and business alignment

Data Engineering Manager: owns engineering execution, platform architecture, and technical delivery

Together, you'll define how your domain evolves while partnering closely with data evaluation, engineering, downstream product teams, and external data partners.

Consumer Receipts: own the systems that process, classify, and validate transaction-level consumer receipt data across millions of purchases.

B2B Spend: own the systems that transform complex mid-market and enterprise purchase and invoice data from multiple providers into standardized, production-ready datasets.

Your success won't be measured by how many analyses you complete. It will be measured by how effectively you've built systems that make hundreds of future analyses faster, more consistent, and more reliable.

Own the lifecycle of your data domain: from defining how raw partner data should be processed, validated, tagged, and modeled to ensuring downstream teams can confidently build products on top of it. Develop deep expertise in your domain and the mental models needed to identify issues before they impact customers.

Build systems that improve data quality: Design validation frameworks, monitoring, and QA systems that proactively detect issues. Reason deeply about representativeness, bias, and systematic risks - not simply whether individual records look correct.

Design reusable methodologies that scale: Identify common business concepts and analytical patterns across Investor, Corporate, and Data Feeds. Build centralized methodologies that reduce duplication, improve consistency, and create lasting leverage across the organization.

Set analytical and technical direction: Partner with the Technical Product Manager to prioritize investments based on cross-business impact, and with the Data Engineering Manager to shape processing architecture and platform capabilities. Make thoughtful tradeoffs between speed, rigor, automation, and long-term scalability.

Expand and evolve your domain: Partner with the Data Evaluation team to onboard new datasets and work directly with technical and business stakeholders at our data providers when needed. Build reusable integration patterns that make future dataset onboarding faster and more reliable.

Redesign analytical work with AI: Use AI, automation, and emerging tooling to fundamentally improve how data is processed, validated, documented, and maintained. Continuously identify opportunities to eliminate manual work and increase the scale and quality of what the team can accomplish.

Help build the organization: As the team grows, mentor junior analysts and establish the standards, processes, and culture that define how your domain operates.

Over your first year, you might:

You have 6-8+ years of experience in data analytics, with a background in fields like financial services, management consulting, data science, or high-growth technology - or another environment where you worked with complex data to drive high-stakes decisions

You have expert fluency in SQL and experience using Python or PySpark, including building reliable, reusable analysis workflows

You have led complex, ambiguous projects with multiple stakeholders - scoping the approach, driving alignment, and delivering outcomes - with a strong bias toward action and ownership

You calibrate rigor to the stakes - you know how much precision a given decision or problem merits, and you don't over- or under-invest

You reason about bias and representativeness, not just averages - you ask whether dropped rows, inconsistent formatting, or gaps in coverage are systematically skewed before drawing conclusions

You're skilled at working with messy, inconsistent datasets and evolving schemas, and you bring the detail-orientation and discipline to make that work reliable

You're energized by the prospect of building — owning a domain end-to-end today, and mentoring and leading junior analysts as the team grows around you

You actively use AI tools and are excited about using AI to drive leverage - not just productivity, but fundamentally better and faster ways of working

Our compensation package includes comprehensive benefits, perks, and a competitive salary:

The annualbasecompensation for this position is anticipated to be $165K-$205K. The final offer may be determined by a number of factors, including, but not limited to, the applicant's experience, knowledge, skills, abilities, as well as 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.

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