In this role, you will work across a highly sophisticated data engine that bridges foundational statistical modeling, complex data infrastructure, and advanced analytical product architecture. Whether your deep expertise lies in refining core statistical baselines, optimizing heavy computational models, or architecting scalable logic libraries, you will have a massive impact on how enterprise-level consumer insights are delivered.

This is a remote-friendly opportunity that can sit in NYC (where our headquarters is located), one of our office hubs, or anywhere else in the US. However, depending upon where the remote work is performed, income could be subject to New York State tax withholding. We expect East Coast work hours.

As Our Corporate Data Scientist, You Will:

• Statistical Modeling & Distribution Optimization: Design, validate, and deploy robust, scalable optimization frameworks and distribution models to ensure complete mathematical integrity across downstream metrics.
• Methodology & Panel Foundations: Explore and execute complex methodologies, evaluate methodological trade-offs, and implement advanced statistical procedures.
• Analytical Logic & Governance: Partner cross-functionally to transition ad hoc code into standardized, version-controlled templates and logical libraries. You will ensure analytics are structured cleanly to power diverse product surfaces, ranging from interactive dashboards to LLM-driven applications.
• Infrastructure & Performance Optimization: Partner closely with Data Engineering to optimize code performance and scale analytical workflows. You will help transition complex statistical calculations from standard database queries into efficient, production-grade cloud compute architectures.

You Are Likely To Succeed If:

• Experience: 4–5 years of professional data science experience. 2-3 years of experience with an advanced degree.
• Education: Bachelor’s degree in a highly quantitative field (Statistics, Economics, Physics, Mathematics, Engineering, or a related discipline). A Master’s degree is strongly preferred.
• Mathematical Proficiency: Exceptional expertise in working with, modeling, and optimizing for statistical distributions.
• Technical Stack: Advanced proficiency in Python or R and expert-level SQL.
• Key Advantages (Big Plus):
• Direct experience working with panel data or longitudinal consumer data.
• Hands-on experience analyzing receipt data or transaction-level consumer data.
• Experience working with Databricks and scaling advanced compute workloads.

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 on-target earnings for this position are anticipated to be up to $170K + bonus element. 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 compensation package also includes equity.

This role may be performed fully remotely within the United States. Please note that our US headquarters are located in NYC. We also have office hubs in Austin, Miami, Denver, Mountain View, and Seattle. 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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Originally posted on Himalayas