Data Analyst

sglottery; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

Scientific Games is seeking a Data Analyst to turn data into reliable, reusable analysis that informs revenue growth, cost reduction, and operational performance across lottery and iLottery platforms.

The role focuses on building cloud-native analysis in Databricks, validating data, and delivering clear, business-ready findings. You will collaborate with business partners, technical teams, and customer stakeholders, applying SQL and Python skills with an emphasis on automation and repeatability.

Qualifications

• Bachelor's degree in a quantitative field. A master's is a plus.
• 3+ years in BI/analytics or related roles.
• Strong SQL skills with multi-source data.
• Experience with Databricks or similar cloud analytics platforms.
• Familiarity with Azure/AWS/Google Cloud patterns.
• Python or similar for analysis and automation.
• GitHub or similar version control with reproducible workflows.
• Design of dashboards and visualizations using BI tools.

Responsibilities

• Create and maintain analyses, reports, dashboards, notebooks, and visualizations.
• Use cloud-native data platforms and Databricks for workflow automation.
• Translate business questions into analytical approaches and actionable recommendations.
• Develop and maintain self-service data products with appropriate visualization tools.
• Collaborate with data engineering and business teams to improve data collection and definitions.
• Review data quality, document assumptions, and communicate findings clearly.
• Produce studies, executive dashboards, and exploratory visualizations to surface insights.

Skills

SQL

Python

Databricks

Version control

Data visualization

Cloud platforms

Education

Bachelor's degree in a quantitative field

Master's degree in data science/analytics (a plus)

Tools

Databricks

GitHub

Tableau/Power BI/Looker/Sigma

Job description

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

The Data Analyst turns data into reliable, reusable analysis that helps internal teams and lottery customers understand performance, identify opportunities, and make better operating decisions. This role supports reporting, dashboarding, exploratory analysis, and recurring analytical workflows with an emphasis on clarity, accuracy, and repeatability. The analyst works with business partners, technical teams, and customer stakeholders to define questions, prepare and validate data, build cloud native analysis in environments such as Databricks, and communicate findings in clear business language. The role requires solid SQL, growing comfort with Python and SQL, familiarity with version control, and an interest in automating routine work so useful analysis can scale without adding unnecessary manual effort.

Key Responsibilities

• Create and maintain analysis, reports, dashboards, notebooks, and visualizations that support revenue growth, cost reduction, operational performance, and customer success.
• Use cloud native data platforms, with emphasis on Databricks, SQL, notebooks, governed datasets, and reusable workflows.
• Help translate business questions into clear analytical approaches, data requirements, success measures, and decision ready recommendations for internal stakeholders and external lottery customers.
• Build and maintain dashboards, reporting assets, and self service data products using the right visualization tool for the need. Tableau experience is helpful, but the role is tool agnostic and values strong visualization judgment over a specific platform version.
• Use GitHub or similar version control practices to manage analytical code, notebooks, documentation, peer review feedback, and reproducible project history.
• Automate recurring analysis, quality checks, data preparation, and distribution steps where practical so the team can deliver more value without adding proportional manual effort.
• Partner with data engineering and business teams to improve data collection, transformation logic, metric definitions, and the usability of shared datasets.
• Review data quality, reconcile source differences, document assumptions, and clearly communicate limitations, confidence levels, and recommended next steps.
• Create and maintain studies, research reports, executive dashboards, sales enablement tools, and exploratory visualizations that surface useful insights and practical growth opportunities.
• Identify process improvement opportunities and contribute to durable solutions that reduce rework, improve trust in the data, and make future analysis easier to repeat.
• Manage multiple analytics tasks and projects, balancing stakeholder requests with clear documentation and reliable analytical practices.
• Work effectively in a remote environment, using collaboration tools, written updates, and shared documentation to keep stakeholders aligned.
• Travel to lottery and corporate locations on an occasional as needed basis.

Qualifications

Required Qualifications

• Bachelor's degree in mathematics, economics, statistics, applied statistics, data science, computer science, engineering, or another quantitative field. A master's degree in data science, applied statistics, analytics, or a related field is a plus.
• At least three years of experience in business intelligence, data analysis, reporting, analytics engineering, data science, or a closely related role.
• Strong SQL skills, including joins, aggregations, filtering, validation, and the ability to work with data from multiple sources.
• Hands on experience, coursework, certification, or practical exposure with Databricks or comparable cloud analytics platforms, including notebook based analysis, lakehouse concepts, Spark SQL, or PySpark.
• Familiarity with cloud native analysis patterns in Azure, AWS, or Google Cloud, including shared workspaces, governed datasets, and scalable compute environments.
• Experience with Python or similar language for analysis, data preparation, automation, or reproducible analytical workflows.
• Familiarity with GitHub or similar version control tools, including commits, branches, pull requests or review workflows, and readable project documentation.
• Ability to design effective dashboards and visualizations in Tableau, Power BI, Looker, Sigma, or comparable BI tools.
• Strong attention to detail and ability t