远程工作雷达

数据负责人 - 中央数据团队

Data Lead - Central Data Team

其他限定地区(需当地身份)
公司yipitdata
薪资未公开
工作地点US Remote
地域资格限定地区(需当地身份)
时区要求无特别要求
用工类型未标注
发布时间2026-08-11
数据来源Greenhouse
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注意地域限制:该职位明确限定在 US Remote 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

关于公司

YipitData 是颠覆性经济领域领先市场研究和分析公司。我们的专有技术分析数十亿个替代数据点,以发现可操作的洞察。全球顶级投资基金和财富500强公司依赖我们的数据来推动高风险决策。

我们在美国、亚太和印度设有办公室。我们获奖的以员工为中心的文化——连续三年被 Inc. 评为最佳工作场所——强调透明度、主人翁意识和持续精进。

在这里工作的体验:

  • 主人翁意识是真实的,而不是空谈。这里的分析师可以全程负责一个数据产品——从方法论到客户交付——并直接向依赖该产品的投资者汇报。你不会花几个月时间等待“有意义的工作”。
  • 成长由影响力驱动,而非资历。你的职责范围和责任随着你证明自己准备好的速度而扩展。我们根据你所做的事来晋升,而不是你在公司的时长。
  • AI 是核心工作工具,而不是附属项目。我们正在积极重建分析工作的流程——使用 AI 代理、自动化和新工具,从根本上改变可能性。如果你对这些感到兴奋,你会在这里茁壮成长。

职位介绍:

YipitData 的中央数据团队是我们所有交付成果的基础。我们构建标准化的数据产品、方法论和系统,为下游业务提供支持——从我们的投资研究和企业产品到我们的数据馈送。

历史上,许多团队独立解决类似的数据问题。中央数据团队的存在是为了识别这些共同模式,并构建共享解决方案,从而在全公司范围内提升质量、一致性和速度。

作为中央数据负责人,你将全程负责其中一个基础数据领域。这是一个高度分析的产品负责人角色,结合了深厚的数据专业知识、系统思维、技术领导力和跨职能执行能力。你不是解决单个分析问题,而是设计可重复使用的系统和方法论,使数十个下游团队能够更快速、更有信心地前进。

每个领域由三人领导团队共同负责:

  • 数据负责人:负责方法论、数据质量和分析策略
  • 技术产品经理:负责优先级排序、路线图和业务对齐
  • 数据工程经理:负责工程执行、平台架构和技术交付

你们将一起工作

查看英文原文

About Us

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.

What It's Like to Work Here:

  • Ownership is 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."
  • Growth is driven by impact, not tenure. Scope and responsibility expand as fast as you can demonstrate you're ready. We promote based on what you've done, not how long you've been here.
  • AI is a core working tool, not a side project. We're actively rebuilding how analytical work gets done - using AI agents, automation, and new tooling to fundamentally change what's possible. If you're excited about that, you'll thrive here.

About the Role:

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.

We're hiring Data Leads for these two teams:

  • 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.

What You'll Do:

  • 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.

Example Projects:

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.

You Are Likely To Succeed If:

  • 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 We Offer:

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

  • We care about your personal life, and we mean it. We offer flexible work hours, flexible vacation, a generous 401K match, parental leave, team events, wellness budget, learning reimbursement, and more!
  • Your growth at YipitData is determined by the impact that you are making, not by tenure, unnecessary facetime, or office politics. Everyone at YipitData is empowered to learn, self-improve, and master their skills in an environment focused on ownership, respect, and trust. See more on our high-impact, high-opportunity work environment above!
  • The annual base compensation 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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