Data Analyst

Scientific Games Corporation; Englewood (CO); Remote; USD 70,000 - 110,000; Full time

Job summary

Scientific Games Corporation seeks a Data Analyst to turn data into reliable, repeatable analysis for internal teams and lottery customers. You will build cloud-native analysis in Databricks, perform SQL-driven analysis, and communicate findings in business language.

Responsibilities include creating dashboards, reports, and self-service data products, using version control with GitHub, and automating recurring workflows to scale insights across the organization.

Qualifications

• Bachelor's degree in mathematics, economics, statistics, data science, computer science, engineering, or another quantitative field.
• 3+ years experience in business intelligence, data analysis, or closely related role.
• Strong SQL skills including joins, aggregations, filtering, and cross-source data work.
• Hands-on experience with Databricks or comparable cloud analytics platforms and notebook-based analysis.
• Familiarity with cloud native analysis patterns on Azure, AWS, or Google Cloud.
• Experience with Python for analysis, automation, or reproducible workflows.
• Familiarity with GitHub or similar version control and project documentation.
• Ability to design effective dashboards in Tableau, Power BI, Looker, Sigma, or similar BI tools.

Responsibilities

• Create and maintain analysis, reports, dashboards, notebooks, and visualizations supporting growth, cost reduction, and performance.
• Use cloud platforms and Databricks to build scalable analytics and reusable workflows.
• Translate business questions into clear analytical approaches, data requirements, and actionable recommendations.
• Develop dashboards and self-service data assets with an appropriate visualization tool.
• Manage analytic code with GitHub, ensuring reproducible project history and peer review.
• Automate recurring analysis and data preparation to increase value with less manual effort.
• Collaborate with data engineering and business teams to improve data collection, transformation logic, and data usability.
• Communicate data quality, assumptions, and limitations clearly to stakeholders.

Skills

SQL

Python

Communication

Dashboards

Data modeling

Education

Bachelor's degree in a quantitative field

Master's in data science / analytics (plus)

Tools

Databricks

Tableau

Power BI

Looker

dbt

GitHub

Airflow

Azure

AWS

Google Cloud

Job description

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.

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 to collect, organize, analyze, interpret, and communicate significant amounts of 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 that support multiple downstream use cases.

Experience automating recurring reporting or analytics workflows with 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.

Skills and Abilities

Think beyond one time deliverables and looks for ways to make each analysis easier to reuse, maintain, audit, and scale.

Balances speed with reliability by documenting assumptions, validating outputs, and building repeatable workflows.

Communicates clearly in writing and conversation with technical teams, business partners, executives, and customer stakeholders.

Works effectively in a team environment, seeks feedback, and contributes to shared analytical standards.

Prioritizes effectively, manages multiple deadlines, and adapts as business needs or data realities change.

Learns new tools, languages, platforms, and analytical methods as needed.

Physical Requirements

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to sit, stand, walk, bend, use hands, operate a computer, and have specific vision abilities to include close and distance vision, and ability to adjust focus working with computer and business equipment.

Work Conditions

Scientific Games, LLC and its affiliates (collectively, “SG”) are engaged in highly regulated gaming and lottery businesses. As a result, certain SG employees may, among other things, be required to obtain a gaming or other license(s), undergo background investigations or security checks, or meet certain standards dictated by law, regulation or contracts. In order to ensure SG complies with its regulatory and contractual commitments, as a condition to hiring and continuing to employ its employees, SG requires all of its employees to meet those requirements that are necessary to fulfill their individual roles. As a prerequisite to employment with SG (to the extent permitted by law), you shall be asked to consent to SG conducting a due diligence/background investigation on you. This job description should not be interpreted as all-inclusive; it is intended to identify major responsibilities and requirements of the job. The employee in this position may be requested to perform other job‑related tasks and responsibilities than those stated above.

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