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Responsibilities

• Build reusable data pipelines and data products across databases, lakehouse and cloud platforms, Anaplan, and other enterprise systems.
• Improve data quality, lineage, orchestration, and performance.
• Maintain and improve existing operational models used for business management.
• Strengthen existing architectures and help new development start with production needs in mind.
• Partner with modelers from prototype onward to turn complex statistical and machine learning models into reliable, maintainable products with appropriate testing, controls, monitoring, documentation, and operational support for forecasting, planning, and scenario design.
• Develop and support practical models for financial planning, with focus on pipeline-style models (for e.g. headcount projections) that can serve as independent challenger models to test business forecasts and identify key assumptions, risks, and alternative outcomes.
• Support production economic scenario generation and other DAG-heavy modeling workflows, making complex calculation graphs scalable, observable, reproducible, and easy for downstream teams to consume.
• Apply agentic development selectively to improve data discovery, model workflows, controls, scenario analysis, and reporting, with appropriate evaluation and safeguards.
• Set pragmatic technical direction and represent a central function across multiple divisions.
• Understand distinct needs, manage senior stakeholders, mediate competing priorities, and build consensus around reusable solutions.
• Review designs and code, mentor practitioners, and maintain a responsive, service-oriented partnership with Finance, Risk, Engineering, and business teams.

Requirements

• Bachelor’s or Master’s degree (U.S. or foreign equivalent) in a quantitative or technical field such as Statistics, Electrical Engineering / Computer Science, Applied Mathematics, Economics, Physics, or Engineering.
• Eight (8) or more years of relevant experience spanning data, modeling, forecasting, financial-planning technology, or software-enabled analytical products.
• A track record of taking ownership of existing operational models, maintaining and improving them for business-management use, and scaling analytical solutions for sustained production.
• Modeling and data practitioners with software fluency.
• Experience improving imperfect real-world models and data.
• Experience solving practical numerical problems.
• Experience moving useful work from local prototypes into dependable shared solutions.

Skills

• Practical Modeling
• Forecasting & Time Series
• Data Engineering & Databases
• Programming & Production
• Planning & Scenario Platforms
• Agentic Development
• Cross-Divisional Leadership
• Strong quantitative judgment
• Exceptional command of practical techniques for working with messy data, limited history, changing business conditions, and operational constraints
• Experience building independent challenger models to assess business projections, test assumptions, and explain differences
• Experience with financial-planning and driver-based models
• Experience building and evaluating forecasts
• Experience selecting fit-for-purpose methods
• Experience diagnosing failure modes
• Experience handling structural change, uncertainty, and unstable real-world series
• Strong SQL
• Data-modeling
• Pipeline
• Orchestration
• Quality
• Lineage skills across relational, analytical, and cloud data platforms
• Experience with lakehouse architectures, Spark, or Databricks is a plus
• Advanced Python and R
• Sound software-development practices
• Hands-on experience taking analytical workflows into scalable cloud production
• Rust is a plus
• Experience connecting models and data to Anaplan or similar planning platforms
• Experience scaling economic scenario generators, simulations, or other dependency-heavy calculation workflows is a major plus
• Working knowledge of agentic systems, including tool integration, orchestration, evaluation, state or context management, and appropriate controls
• Demonstrated experience operating from a central function and delivering for multiple divisions
• Strong service orientation and stakeholder-management skills
• Credibility to reconcile competing needs, mediate trade-offs, build consensus, and connect technical decisions to shared business outcomes

Experience Level

• Eight (8) or more years of relevant experience

Education Level

• Bachelor’s or Master’s degree (U.S. or foreign equivalent) in a quantitative or technical field