YipitData is the leading market research and analytics firm for the disruptive economy and most recently raised $475M from The Carlyle Group at a valuation of over $1B. Every day, our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like software, AI, cloud, e-commerce, ridesharing, and payments. We operate globally with offices in the US (NYC, Austin, Miami, Mountain View), APAC (Hong Kong, Shanghai, Beijing, Guangzhou, Singapore), 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.
Data Analyst II
Location
United States
Posted
3 days ago
Salary
$165K - $185K / year
Seniority
Mid Level
Job Description
Data Analyst II
YipitData (Alternative)
Role Description You'll be joining the data feeds part of our organization, focusing on Kepler, a tractions feed that tracks over $45 billion in US consumer transactions across 600+ merchants and 200+ tickers. As a Data Analyst for Kepler, you'll ramp quickly and build deep expertise in our third-party and proprietary datasets and methodologies. Working closely with customers, Product, Data Science, and Engineering, you'll take full ownership of the Kepler data — ensuring accuracy, improving methodologies, implementing QA frameworks, and prototyping enhancements that engineering will turn into robust, reliable data pipelines. This is a role for someone who wants to go deep on hard analytical problems, takes pride in getting the details right, and is motivated by owning work that matters. You'll work cross-functionally with teams across the organization to deliver best-in-class outputs. You'll also be expected to bring ideas, not just execute on others. This is a remote-friendly opportunity that can sit in NYC (where our headquarter is located), one of our office hubs, or anywhere else in the US. - Own Kepler data content end-to-end — driving product success by delivering best-in-class outputs with a focus on accuracy, and continuously increasing client value. - Work with massive amounts of data and develop deep expertise in our proprietary methods and techniques, building strong mental models that allow you to ensure data accuracy, identify methodology gaps, and derive key insights. - Tackle complex data problems using strong analytical judgment to refine methodologies, test new datasets, and solve challenges that require creative thinking — even when information is incomplete or ambiguous. - Use AI and tooling to drive meaningful leverage — increasing speed, reducing manual work, and automating portions of workflows. You'll build repeatable processes, maintain a high bar for correctness and quality, and validate AI-generated outputs. - Use AI to drive client-value — you will write prompts and run automated evaluation processes to ensure our client-facing Kepler Insight Agent is accurate and able to answer the questions our customers are asking. - Collaborate cross-functionally with Research, Engineering, and other teams — coordinating across functions to unblock work, align on best practices, and develop solutions that streamline workflows and optimize data processes. - Help our customers understand the data by handling high-complexity questions about anomalies and trends in the data that our first line of support can’t handle. Qualifications - 4-6+ years of experience in data analytics, with a background in fields like financial services, management consulting, data science, or high-growth technology. - Expert fluency in SQL and experience using Python or PySpark, including building reliable, reusable analysis workflows. - A proven track record of quickly learning complex data methodologies and building strong mental models of how and why data works. - Experience leading complex, ambiguous projects with multiple stakeholders — scoping the approach, driving alignment, and delivering outcomes. - Ability to clearly communicate complex concepts — including methodology, risks, and tradeoffs — and influence cross-functional partners to move decisions forward. - Active use of AI tools and excitement about using AI to drive leverage. Requirements - Strong analytical judgment and problem-solving skills. - Experience with data accuracy and methodology refinement. - Ability to work cross-functionally and collaborate effectively. Benefits - Flexible work hours and flexible vacation. - Generous 401K match and parental leave. - Team events and wellness budget. - Learning reimbursement. - Compensation package includes a competitive salary, with an anticipated annual base compensation of $165K-$185K. - Opportunity for remote work within the United States.
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• Own Kepler data content end-to-end — driving product success by delivering best-in-class outputs with a focus on accuracy, and continuously increasing client value. • Work with massive amounts of data and develop deep expertise in our proprietary methods and techniques, building strong mental models that allow you to ensure data accuracy, identify methodology gaps, and derive key insights. • Tackle complex data problems using strong analytical judgment to refine methodologies, test new datasets, and solve challenges that require creative thinking — even when information is incomplete or ambiguous. • Use AI and tooling to drive meaningful leverage — increasing speed, reducing manual work, and automating portions of workflows. You'll build repeatable processes, maintain a high bar for correctness and quality, and validate AI-generated outputs. • Use AI to drive client-value — you will write prompts and run automated evaluation processes to ensure our client-facing Kepler Insight Agent is accurate and able to answer the questions our customers are asking. • Collaborate cross-functionally with Research, Engineering, and other teams — coordinating across functions to unblock work, align on best practices, and develop solutions that streamline workflows and optimize data processes. • Help our customers understand the data by handling high-complexity questions about anomalies and trends in the data that our first line of support can’t handle.
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