[Remote] Sr. Data Scientist

Note: The job is a remote job and is open to candidates in USA. Cypress HCM is seeking a Senior Data Scientist to join their Finance Data Science & Strategy team. This role involves building and maintaining forecasting models that inform Treasury and Finance decisions, requiring hands-on expertise and the ability to translate complex data into actionable insights for non-technical partners.

Responsibilities

• Build and maintain a portfolio of statistical forecasting models segmented by account characteristics to support Treasury's funding schedule
• Improve forecast accuracy across cash flow directions, prioritizing the areas where funding decisions are most sensitive
• Bring financial planning signals such as cancellations, revenue, and seasonality into the models as covariates, and account for the effect of macro shocks and product changes on user behavior
• Preserve forecast accuracy when Treasury reallocates volume across accounts
• Run diagnostics after each production cycle to explain what drove a miss, where the forecast fell short, and what fixes are planned
• Support the analysis behind manual adjustments to the forecasts
• Serve as the embedded data science partner for Treasury, translating model behavior into terms partners can act on and staying engaged on funding decisions week to week
• Monitor the data workflow for missing or mismatched records, and maintain the pipelines that populate the forecasting tables and reporting dashboards

Skills

• 5+ years of industry experience in a forecasting or quantitative analysis role with a Master's degree in a quantitative field (computer science, statistics etc.), or 2+ years of experience with a Ph.D
• Strong hands-on expertise in SQL and at least one programming language (Python or R)
• Proven experience building and maintaining production time series or statistical forecasting models, including handling structural breaks, interventions, and external shocks
• Experience integrating covariates and external signals into forecasts and validating their contribution
• Experience owning data pipelines end to end, including scheduling, orchestration, and reporting layers
• Strong analytical judgment, with the ability to balance rigor against the speed a recurring production cadence demands
• Demonstrated ability to operate independently, manage multiple workstreams, and deliver against a fixed calendar
• Strong stakeholder communication skills, with a track record of translating model behavior into decisions non-technical partners can act on
• Experience with finance, treasury, or marketplace data strongly preferred
• Familiarity with AI-assisted analytics workflows is a plus

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