Director, Data Science & Engineering (Finance)

Quick Facts

• Role: Director, Data Science & Engineering (Finance)
• Team: Leads a multidisciplinary team (data scientist + data engineer)

Description

This is a leadership role at the intersection of data science, data engineering, finance, and AI. You will build trusted data and robust analytical systems so Finance can make better decisions through applied modeling and increasingly AI-powered capabilities. You will set strategy and priorities, provide technical leadership across both disciplines, and deliver durable business impact.

Responsibilities

• Manage and grow a multidisciplinary team; coach, delegate, and build a culture of ownership and continuous improvement
• Translate Finance/company goals into a prioritized portfolio across recurring operations, driver-model maintenance, knowledge coordination, and technical debt
• Provide technical leadership across data science and data engineering (problem framing, architecture, pipelines, testing, monitoring, documentation, production readiness)
• Advance AI and modeling capabilities for Finance workflows, including standards for experimentation, evaluation, interpretability, human oversight, privacy, and monitoring
• Build trusted data foundations: improve source-of-truth datasets, data quality, lineage, observability, documentation, and reliability
• Own analytical and modeling outcomes for planning, forecasting, and driver-based decision support; connect results to measurable business outcomes
• Create scalable operating mechanisms for intake, roadmap planning, reviews, incident response, knowledge sharing, and stakeholder communication
• Influence Finance and senior stakeholders by communicating implications, recommendations, risks, and trade-offs clearly
• Partner across functions to align priorities and approaches; lead debate and stakeholder alignment
• Continuously improve scope and effectiveness by eliminating low-value work, automating recurring tasks, improving service levels, and transforming the operating model when needed

Requirements

• Bachelor’s degree or above in a quantitative field (Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, etc.) or equivalent practical experience
• Significant experience applying data science, machine learning, analytics, and/or data engineering to business problems
• Experience managing and developing technical professionals, ideally including data scientists and data engineers (or closely adjacent roles)
• Strong professional foundation in either data science or data engineering, with demonstrated ability to work effectively across the other discipline
• Experience leading a portfolio of projects from problem definition through delivery, adoption, measurement, and ongoing operation
• Experience with data quality, data pipelines, analytical datasets, model development/maintenance, experimentation/evaluation, and production/operational support
• Demonstrated ability to use data and technology to influence business decisions and deliver measurable impact
• Strong communication and stakeholder-management skills, including explaining technical concepts, uncertainty, and trade-offs to Finance and executives
• Demonstrated growth mindset and ability to adapt to changing conditions
• Ability to operate with high autonomy and ownership in an ambiguous, fast-changing environment

Benefits

• Competitive compensation (US Zone 2: $228,400–$309,000 USD; US Zone 3: $203,000–$274,600 USD)