Director, Finance Systems & AI

Responsibilities

• Finance Data Architecture. Partner with the data team and finance leadership to finish building out the finance domain of our central data warehouse. Define source-of-truth datasets, semantic models, and data contracts. Drive accuracy, freshness, and trust as non-negotiables.
• Team Leadership. Manage and grow the inherited team. Coach, hire, and set the bar for both engineering rigor and finance fluency.
• Cross-Functional Partnership. Work daily with the finance/FP&A team, the data/analytics engineering team, and the executive team. Translate ambiguous business questions into durable data products.

Requirements

• This role calls for a rare hybrid - someone equally comfortable in a data warehouse, a Python notebook, and an FP&A review meeting. We expect candidates to bring strength in at least two of the three areas below, with working knowledge of the third:
• Data & analytics engineering. You've built and maintained production data pipelines and semantic models. SQL is second nature.
• Finance / FP&A. You understand how a P&L is built, how forecasts are constructed, and how operators think about driver-based planning.
• Internal tool building. You've shipped internal finance or analytics tools - not just dashboards, but real applications people depend on.
• Must-Have Skills
• Expert SQL and hands-on experience with a modern cloud data warehouse (Snowflake, BigQuery, Databricks, or equivalent)
• Strong Python and modern data modeling tooling (dbt or equivalent)
• Demonstrated experience building with AI/LLM tooling - APIs, agents, RAG architectures, evals
• Track record of designing, shipping, and operating internal data products or applications used by non-technical stakeholders
• People management experience and the ability to coach a team across the data/finance spectrum
• Strong written and verbal communication, especially in executive settings
• Prior experience in an FP&A, strategic finance, or finance systems role
• Experience with forecasting / EPM platforms (Pigment, Anaplan, Cube, Workday Adaptive, etc.) as a build-on-top layer
• Front-end development experience (HTML/CSS/JavaScript) - relevant to our in-house dashboarding platform
• Experience standing up data governance, data contracts, or finance close automation
• What Success Looks Like
• First 90 days: Establish trust with the finance, data, and executive teams. Audit the current state of the finance data layer, dashboarding tool, and forecasting process. Deliver a sequenced roadmap.
• First 6 months: Complete the finance domain of the data warehouse. Ship the first generation of AI-enabled self-service dashboards. Stand up the v1 of the forecasting hub for at least one business unit.
• First 12 months: Forecasting hub adopted company-wide with full stage-gating, approvals, and scenario memorialization in the warehouse. AI agents are a routine part of how finance and operators interact with data. Team is operating with clear ownership and a strong delivery cadence.
• Physical Requirements
• The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonab

Additional Information

Scientific Games: Scientific Games is the global leader in lottery games, sports betting and technology, and the partner of choice for government lotteries. From cutting-edge backend systems to exciting entertainment experiences and trailblazing retail and digital solutions, we elevate play every day. We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation, legendary performance, and unwavering security to responsibly propel the global lottery industry ever forward. Position Summary

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at sglottery? Share your experience