# Staff Applied Scientist, Financial Forecasting

**Company:** [Vercel](https://hotfix.jobs/companies/vercel)
**Location:** San Francisco, CA, New York, NY
**Role:** Data Science
**Salary:** $250k – $330k/yr
**Experience:** 8+ years
**Skills:** Python, SQL, Time-Series Forecasting, Deep Learning, Bayesian Modeling, Probabilistic Modeling, Hierarchical Reconciliation, Causal Inference, Experimentation Design, Machine Learning, Snowflake, Delta Lake, dbt, Airflow, MLOps
**Posted:** 2026-08-25

> Leads the architecture and productionization of advanced consumption forecasting systems supporting financial planning, infrastructure capacity, and executive decisions. Requires staff-level technical leadership, deep time-series and causal modeling expertise, and strong Python and SQL skills.

## Job Description

## Responsibilities
- Architect and own end-to-end consumption forecasting ML systems across compute, bandwidth, edge functions, storage, and emerging products.
- Design and productionize advanced time-series forecasting approaches, including deep learning, probabilistic/Bayesian, hierarchical, and hybrid statistical-ML architectures.
- Develop multi-horizon forecasts for operational, quarterly, and long-range planning, reconciling predictions across account, cohort, segment, and global levels.
- Build infrastructure for backtesting, monitoring, drift detection, and forecast explainability.
- Develop scenario simulation and causal inference frameworks for pricing changes, packaging adjustments, and product launches.
- Partner with Finance leadership on board-level reporting and revenue planning, and with Infrastructure Engineering on capacity planning and cost optimization.
- Model adoption curves, expansion dynamics, and usage drivers with Product and GTM teams.
- Set ML methodology, experimentation, and measurement standards; mentor senior data scientists and ML engineers.

## Requirements
- 8+ years of experience in machine learning, data science, or applied statistics, with staff- or principal-level experience.
- Advanced time-series forecasting and ML modeling expertise, including deep learning forecasting architectures, Bayesian/probabilistic modeling, and hierarchical reconciliation.
- Experience architecting and productionizing ML systems at scale, including training, serving, monitoring, and retraining infrastructure.
- Strong Python and SQL proficiency and experience with large-scale usage and billing datasets.
- Strong grounding in causal inference and experimentation design.
- Experience setting technical direction and partnering with Finance or executive leadership on planning cycles.
- Technical leadership experience, including setting standards, mentoring senior individual contributors, and influencing organizational ML practices.
- Ability to define ambiguous, high-stakes problems autonomously and communicate advanced ML concepts to non-technical audiences.
- Experience with cloud infrastructure, developer tools, or consumption-based revenue models.

## Nice to Have
- Capacity planning or cost modeling experience at scale.
- Experience with Snowflake, Delta Lake, dbt, Airflow, feature stores, or MLOps tooling.
- Experience as a technical lead for a data science or ML team without formal management authority.

## Compensation and Benefits
- San Francisco, CA base pay range: **$250,000–$330,000**.
- Competitive compensation package, including equity.
- Inclusive healthcare package.
- Mentorship and professional development opportunities, including industry events.
- Flexible time off.
- Company-provided equipment and a work-from-home budget.

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