Data Analyst

Scientific Games; Centennial (CO); Remote; USD 75,000 - 105,000; Full time

Job summary

Scientific Games is seeking a Data Analyst to turn data into reliable, reusable analyses that guide internal teams and lottery customers. You will create dashboards, reports, and notebooks, working with Databricks and cloud platforms to deliver repeatable analytics and actionable insights.

The role emphasizes accuracy, clear communication, and the ability to automate recurring analyses while collaborating with data engineering and business teams. Occasional travel may be required.

Qualifications

• Bachelor’s degree in a quantitative field or closely related discipline.
• At least three years of experience in BI, data analysis, or analytics engineering.
• Strong SQL skills with joins, aggregations, filtering, and data from multiple sources.
• Hands-on experience with Databricks or cloud analytics platforms and notebooks.
• Experience with Python for analysis, automation, or reproducible workflows.

Responsibilities

• Create and maintain analysis, reports, dashboards, notebooks, and visualizations to support growth and performance.
• Translate business questions into analytical approaches with measurable outcomes.
• Build and maintain dashboards and self-service data products using BI tools.
• Collaborate with data engineering to improve data collection and metric definitions.
• Review data quality, reconcile source differences, and communicate limitations.
• Automate recurring analyses and reporting workflows to reduce manual effort.

Skills

SQL

Python

Databricks

GitHub

Tableau

Power BI

Education

Bachelor's degree in a quantitative field

Tools

Databricks

dbt

Airflow

Azure Data Factory

Alteryx

Job description

The Data Analyst role at Scientific Games focuses on turning data into dependable, reusable analysis that helps internal teams and lottery customers understand performance, uncover opportunities, and support better operational decisions. The position emphasizes clarity, accuracy, and repeatability across reporting, dashboarding, exploratory analysis, and recurring analytical workflows.

Responsibilities

• Create and maintain analysis, reports, dashboards, notebooks, and visualizations that support revenue growth, cost reduction, operational performance, and customer success.
• Work with cloud native data platforms, with emphasis on Databricks, SQL, notebooks, governed datasets, and reusable workflows.
• Translate business questions into analytical approaches, including 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 appropriate visualization tool for each use case.
• 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 to reduce 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 communicate limitations, confidence levels, and recommended next steps.
• Create and maintain studies, research reports, executive dashboards, sales enablement tools, and exploratory visualizations that surface actionable insights.
• 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 by 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 maintain stakeholder alignment.
• Travel to lottery and corporate locations on an occasional basis as needed.

Requirements

• Bachelor’s degree in a quantitative field, such as mathematics, economics, statistics, applied statistics, data science, computer science, engineering, or a related discipline.
• 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 working 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 a 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, including the ability to collect, organize, analyze, interpret, and communicate information accurately.
• Ability to explain analytical findings, tradeoffs, and recommendations in plain language for business, executive, and customer audiences.

Preferred Experience

• Experience contributing to reusable data models, metric layers, feature datasets, or certified analytical tables supporting multiple downstream use cases.
• Experience automating recurring reporting or analytics workflows using scheduled jobs, orchestration tools, notebooks, scripts, or CI style validation.
• Working knowledge of data quality practices, testing approaches, lineage, documentation, and governance in modern analytics environments.
• Experience with Alteryx, dbt, Airflow, Azure Data Factory, or similar transformation and orchestration tools.
• Familiarity with forecasting, segmentation, regression, classification, or other statistical methods used in practical business analysis.
• Experience supporting sales, operations, gaming, lottery, retail, or other transaction-rich business domains.

Technologies

• SQL, Python, Databricks, Spark SQL, PySpark
• Azure, AWS, Google Cloud
• GitHub
• Tableau, Power BI, Looker, Sigma

Skills and Abilities

• Think beyond one-time deliverables by making analysis easier to reuse, maintain, audit, and scale.
• Balance speed with reliability through documented assumptions, validated outputs, and repeatable workflows.
• Communicate clearly in writing and conversation with technical teams, business partners, executives, and customer stakeholders.
• Work effectively in a team environment by seeking feedback and contributing to shared analytical standards.
• Prioritize effectively, manage multiple deadlines, and adapt as business needs or data realities change.
• Learn new tools, languages, platforms, and analytical methods as needed.

Physical Requirements

Regularly required to sit, stand, walk, bend, use hands, operate a computer, and have specific vision abilities including close and distance vision, plus the ability to adjust focus while working with computer and business equipment.

Work Conditions

• Scientific Games, LLC and its affiliates are engaged in highly regulated gaming and lottery businesses.
• Certain SG employees may be required to obtain a gaming or other license(s), undergo background investigations or security checks, or meet standards required by law, regulation, or contracts.
• As a condition to hiring and continuing employment, SG requires employees to meet the requirements necessary to fulfill their individual roles.
• As a prerequisite to employment with SG (to the extent permitted by law), you may be asked to consent to SG conducting a due diligence/background investigation.