Director, Finance Systems & AI

Scientific Games•Alpharetta, GA

About The Position

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 What You'll Own 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. In-House Dashboarding Platform. Lead the design, development, and ongoing maintenance of our homegrown HTML-based dashboarding tool. We're building in-house to keep costs low and retain full control over UX and AI integration. You'll set the technical direction, ship self-service dashboards that finance partners and executives actually use, and ensure every number ties out. AI Coordination & Agent Design. Design the AI layer that turns our warehouse into a conversational, self-service experience. Spec and build AI agents that help users explore data, generate commentary, automate variance analysis, and answer ad-hoc finance questions. Own the prompts, the retrieval architecture, the evaluation framework, and the deployment pipeline. Finance Hub & Forecasting Application. Build a new forecasting and budgeting hub in collaboration with operators and business owners. The application will support a structured workflow — input gathering, stage-gated review, approvals, and final commit — and memorialize every scenario in the data warehouse for full historical traceability. We'll take a hybrid build approach: a custom UI tailored to our processes, layered on top of an existing modeling engine. 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

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

Nice To Haves

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

Responsibilities

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.
Lead the design, development, and ongoing maintenance of our homegrown HTML-based dashboarding tool.
Set the technical direction for the dashboarding tool, ship self-service dashboards that finance partners and executives actually use, and ensure every number ties out.
Design the AI layer that turns our warehouse into a conversational, self-service experience.
Spec and build AI agents that help users explore data, generate commentary, automate variance analysis, and answer ad-hoc finance questions.
Build a new forecasting and budgeting hub in collaboration with operators and business owners.
Manage and grow the inherited team.
Coach, hire, and set the bar for both engineering rigor and finance fluency.
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.