Data Scientist

Job Description

Job Description

Description:

Vast builds the operating and financial backbone for fast-growing, cash-intensive businesses, combining hands-on execution with purpose-built software, automation, and AI-enabled workflows. We provide technology-enabled shared services, financial infrastructure, and operational support to partners across the U.S. and Puerto Rico, with deep roots in route gaming and other multi-location businesses. We work execution-first, with accurate books, strong controls, and dependable processes, then build the automation and software that raise the standard for how the back office operates.

About the Role

One of the biggest partners we support is a video gaming terminal route across Illinois: machines in bars, restaurants, and truck stops, serviced by field technicians, collected by dedicated crews, supported by a call center, and run on a platform we build and maintain. Every piece of that operation throws off data, and far less of it gets used than should. This role exists to close that gap. Not by producing more charts, but by turning that data into finished work: dashboards that answer a real question, and worklists that tell a specific person what to do Monday morning.

This is not a reporting desk. If the job becomes "run this query for me," we built it wrong. It is not a research role either. Elegance is nice, but a route that runs two hours shorter is better. You will sit close to the operation and to the product and engineering teams building its platform, and your work ships into that live platform, not beside it, and the highest-value work here will be the things nobody thought to request.

What You'll Own

You will work across a deep, multi-year data estate: 250+ Illinois locations, machine and game-level performance, cash and service routing, technician dispatch, the project pipeline, call center volume, and public state reporting. Far more signal than currently gets used.

• Finished analysis, not raw ingredients. A clear answer, the reasoning, and a recommendation someone can act on. Not a table dump.
• Dashboards people open on purpose. Built into the system of record, in our design system, answering questions the regional directors, ops leads, and executives running the route already ask. If nobody opens it twice, it did not work.
• Worklists, the part we care most about. Ranked, assignable lists: the specific machines, locations, or routes that need attention this week, in priority order, with the recommended move and the value of making it. Underperforming machines, wrong collection cadences, equipment to repair or replace, ground lost to nearby competition. A short list, ordered by impact, that an operator can work through.
• Models where they earn their keep. Forecasting, route and schedule optimization, anomaly detection, siting and expected-performance models. Applied, not academic. We care about the decision it changes.

What Success Looks Like

• First 30 days: You know the data model, the metrics, and where the bodies are buried in the data. You have been in the field at least once.
• First 90 days: At least one dashboard and one worklist in real use, with an owner who relies on it.
• First year: Decisions across game mix, routing, staffing, and project prioritization are measurably better because of work you initiated, including work nobody asked for.

• A self-starter with an appetite for data. The best version of this hire goes looking: pulls the state's public reporting because they wondered how the operation stacks up, notices a Tuesday-evening pattern nobody asked about and chases it down, shows up to the meeting with the artifact already built. If you need a fully specified ticket before you start, this will be frustrating for both of us.
• Fluent in the business, not just the numbers. You will talk to regional directors, technicians, collectors, and the call center, then go to the data with a better question.
• Comfortable in a fast environment where priorities move and data is not always clean. You can tell which questions need a rigorous answer and which need a good-enough answer by Thursday.
• 3+ years in data science, analytics engineering, or quantitative analysis with real operational impact.
• Advanced SQL: window functions, CTEs, query tuning, and the judgment to work confidently in messy production data without hand-holding.
• Data modeling: you can design schemas, define grain, build fact and dimension structures, and turn transactional systems into analysis-ready models.
• Data warehousing: standing up and maintaining a warehouse or analytical layer, including ETL/ELT pipelines, incremental loads, and data quality checks.
• Data visualization with a real point of view on chart selection, encoding, and when a number in a box beats a chart entirely.
• Dashboarding and UI/UX design: layout, hierarchy, filter design, progressive disclosure, and mobile legibility are part of the job, not polish added at the end.
• Experience in a modern BI or analytics platform (Tableau, Power BI, Looker, Metabase, Superset, Sigma, Quicksight, or comparable). We care that you have shipped and maintained real reporting for real users, not which tool taught you that.
• Python or R for analysis and modeling (pandas, scikit-learn, or equivalent).
• Forecasting and time-series analysis: seasonality, day-of-week and hour-of-day demand patterns, and the judgment to know when a trend is signal and when it is noise.
• Geospatial analysis: clustering, drive-time and distance modeling, coverage and territory analysis. Route or network optimization experience is a strong plus, since routing is core to how the operation runs.
• Metric definition and stewardship: you can pin down what a metric means, defend the definition, and keep it from quietly forking into three versions across the business.
• A track record of taking an ambiguous business question and returning a defensible, actionable answer, and explaining a model to someone who will never look at the code.

Highland Holdings and its portfolio companies are equal opportunity employers. We evaluate all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.

We offer a full suite of benefits, including medical, dental, vision, 401(k) matching, and more.