Data Analyst: Revenue Insights & Automated Dashboards

Scientific Games; Colorado; On-site; USD 85,000 - 120,000; Full time

Job summary

Scientific Games is seeking a Data Analyst to turn data into reliable analyses for internal teams and lottery customers. You will build cloud-native analyses in environments like Databricks, with solid SQL, growing Python skills, and a focus on clear, business-ready findings.

Expect dashboards, data products, and automated pipelines to support revenue growth and operational metrics. You will collaborate with data engineering and business teams, translate questions into measurable analyses, and

Qualifications

• Bachelor's degree in mathematics, economics, statistics, data science, CS, or a quantitative field.
• Master's degree in data science, analytics, or related field is a plus.
• 3+ years in BI, data analysis, reporting, or analytics engineering.
• Strong SQL skills with multi-source data experience; Databricks expertise preferred.

Responsibilities

• Create and maintain analyses, dashboards, notebooks, and visuals for revenue, costs, and operations.
• Translate business questions into analytical approaches and decision-ready recommendations.
• Build reusable data products and self-service dashboards using appropriate BI tools.
• Use GitHub or similar to manage code, notebooks, and documentation with reproducible history.
• Automate recurring analytics and quality checks to scale insights with minimal manual effort.

Skills

SQL

Python

Databricks

GitHub

Tableau

Education

Bachelor's degree in a quantitative field

Master's degree in data science or related field

Tools

Databricks

Azure

AWS

Job description

Scientific Games is seeking a Data Analyst to turn data into reliable analyses for internal teams and lottery customers. You will build cloud-native analyses in environments like Databricks, with solid SQL, growing Python skills, and a focus on clear, business-ready findings.

Expect dashboards, data products, and automated pipelines to support revenue growth and operational metrics. You will collaborate with data engineering and business teams, translate questions into measurable analyses, and