Data Lead, YipitData
Central Data Team
$170-185k
+ Equity
SQL
Python
Senior and Expert level
Remote from US
Alternative data driven market & investment research firm
Posted today
Alternative data driven market & investment research firm
501-1000 employees
FintechB2BInvestingAnalyticsMarket researchFinancial ServicesSaaSCapital Markets
Posted today
$170-185k
+ Equity
SQL
Python
Senior and Expert level
Remote from US
501-1000 employees
FintechB2BInvestingAnalyticsMarket researchFinancial ServicesSaaSCapital Markets
Company mission
To usher in the new era of market research.
Role
Who you are
- 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 a proven track record of quickly learning complex data methodologies and building strong mental models of how and why data works
- 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 can clearly communicate complex concepts — including methodology, risks, and tradeoffs — and influence cross-functional partners to move decisions forward
- 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
What the job involves
- 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:
- Central 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
- 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:
- Design a generalized methodology for classifying millions of receipt line items across multiple data providers
- Build automated QA systems that detect systematic shifts in merchant tagging before they impact downstream products
- Develop reusable frameworks that reduce the time required to onboard new datasets from months to weeks
- Partner with Engineering to redesign processing architecture that improves scalability while reducing operational overhead
- Create standardized business logic that replaces multiple inconsistent implementations used across different business units
Our take
Annual expenditure on data sets amongst US asset managers has grown to over $1 Billion since the turn of the decade, and is only increasing. Alternative data providers like YipitData are providing answers to such investors.
By focusing on disruptive, digital-first sectors, the company provides maximum value to their clients. This is because, in recent times, many of the highest-growth opportunities have been the hardest to price. By supporting this pricing, YipitData is a stand-out.
Thus, the company has emerged as a leading provider of highly accurate and detailed research and analytics in the rapidly evolving landscape of disruptive and digitally enabled sectors. With an impressive client base in the hundreds and significant funding behind it, YipitData is poised to expand innovation and venture into new markets.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Top investors
Company
Funding (last 2 of 5 rounds)
Dec 2021
$475m
SERIES E
May 2019
$85m
LATE VC
Total funding: $577m
Company benefits
- Flexible work hours
- Flexible vacation
- Generous 401K match
- Parental leave
- Team events
- Wellness budget
- Learning reimbursement
Company HQ
Midtown South, New York, NY
Leadership
Vinicius Vacanti
(Founder & CEO)Prior to YipitData, they were an Associate at Quadrangle Group and an Analyst at The Blackstone Group.
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