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YipitData

Head of Data, Private Investor

RemoteUnited States only
Published
Role
Data Science
Experience
C-Level
Employment
Full-time
Company size
Enterprise
$230k–$250k/yr
Check eligibility

Open to US only. Set where you work from to check your eligibility.

No BS summary

Data leader with 8+ years in data-intensive roles, owning data quality and methodology for a data product. Must be hands-on with SQL, data pipelines, QA frameworks, AI/LLM data problems, and scaling analyst teams. US-only, remote-friendly, East Coast hours; no visa sponsorship.

Core skills

SQLLLMsData pipelines

What you'll do

  • Own data methodology, quality, and accuracy for private-company insights.
  • Lead work that gives investors confidence in how private AI and Software companies are performing.
  • Dig into and redefine existing business logic that stitches together first- and third-party datasets.
  • Build on benchmarking data to drive better accuracy.
  • Hire, mentor, and manage a high-caliber team of data analysts as the function scales.
  • Own trust of AI and Software data end-to-end.
  • Act as the single accountable owner for data coverage and accuracy.
  • Determine where data quality across breadth, depth, accuracy, and speed is sufficient or insufficient.
  • Improve data quality using the company's in-house data sources.
  • Set data strategy and prioritization.
  • Determine which internal and external data sources and enrichment streams to invest in.
  • Optimize accuracy, coverage, cost, and complexity tradeoffs for dataset investment.
  • Optimize business logic for blending data sources into existing data assets.
  • Partner with partnerships, product, and data engineering teams.
  • Design and maintain a world-class QA system.
  • Build truth data benchmark sets and a QA framework to continuously monitor and improve accuracy.
  • Scale the data function from 1 to 10.
  • Start as a player-coach with a small team of analysts.
  • Build a team and culture that fosters data excellence at scale.
  • Contribute to cutting-edge uses of AI in data.
  • Partner with upstream AI and Data Engineering teams to drive scaled entity resolution via AI-tagging systems.
  • Ensure source data accuracy systematically improves.
  • Lead pipeline business logic design.
  • Work hands-on with data pipelines to author refactor specs.
  • Define panelization and outlier handling.
  • Reduce data lag.
  • Help create maintainable pipelines and workflows balancing scale and coverage against downstream accuracy and depth.
  • Serve as the data authority for private investor customers.
  • Lead accuracy escalations and investigations.
  • Support sophisticated customer diligence.
  • Translate data methodologies and outputs into digestible end-customer communication that builds trust.

What they require

  • 8+ years in data-intensive roles, with a track record owning data quality and methodology for a data product.
  • Ideally experience with a data product used by investors or other highly analytical end customers.
  • Experience building and scaling a data function, growing a team from early stage to meaningful scale.
  • Player-coach who is excited to do the work personally and able to build and develop new analysts.
  • Deep technical fluency and hands-on instincts.
  • Ability to investigate data anomalies to root cause.
  • Ability to design, pressure-test, or critique pipeline architecture.
  • Enjoys getting close to the data.
  • Experience applying AI / LLMs to messy data problems such as tagging, classification, entity resolution, or enrichment.
  • Practical understanding of how to evaluate, improve, and govern AI / LLM data systems.
  • Naturally skeptical of data quality and knows where quality standards need to be uncompromising.
  • Balances data quality standards with a bias for delivering to customers.
  • Can judge when output is good enough.
  • Strong prioritization instincts and judgment to make tradeoff decisions across accuracy, cost, speed, and customer impact.
  • Clear communication skills.
  • Can describe ambiguous data challenges and explain in writing and verbally what needs to be done next and why.
  • Comfort engaging directly with end users.
  • Can handle sophisticated client conversations covering methodology and data trust.
  • Expected to work East Coast work hours.
  • Must not currently or in the future require visa sponsorship.
  • Preferred: Experience working with investor clients.

Benefits

  • Flexible work hours.
  • Flexible vacation.
  • Generous 401K match.
  • Parental leave.
  • Team events.
  • Wellness budget.
  • Learning reimbursement.
  • Annual performance-based bonus of up to 15% base salary.
  • Equity.
  • Remote work within the United States.
  • Growth determined by impact, not tenure, unnecessary facetime, or office politics.
  • Environment focused on ownership, respect, and trust.

YipitData is a market research and analytics firm whose proprietary technology analyzes alternative data to deliver insights for clients including investment funds and Fortune 500 companies.

🇺🇸 United StatesMarket Research And AnalyticsEnterprise

Details

Visa sponsorshipNo
Apply routeGreenhouse
$230k–$250k/yr