Domino's

Data Scientist

Domino's$80K — $95K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 1-3 years of experience in data science or analytical roles.
  • Degree in a quantitative field (Computer Science, Statistics, Mathematics, or Engineering).
  • Proficiency in data manipulation and analysis using Python and SQL.
  • Familiarity with geospatial data tools (ArcGIS, Pandas, GeoPandas).
  • Basic understanding of machine learning algorithms and concepts.

Responsibilities

  • Conducts data collection, cleaning, and preprocessing for analysis.
  • Develops and implements statistical models and machine learning algorithms.
  • Collaborates with cross-functional teams to deliver actionable insights.
  • Documents methodologies for reproducibility and knowledge sharing.
  • Monitors model performance and maintains data pipelines.

Benefits

  • Paid holidays and vacation.
  • Medical, dental, and vision benefits starting on the first day.
  • No-cost mental health support for employees and dependents.
  • Childcare tuition discounts.
  • No-cost fitness, nutrition, and wellness programs.
  • Fertility benefits and adoption assistance.
  • 401k matching contributions.
  • 15% off stock purchases and company bonuses.
Full Job Description
Job Description

Drive new store openings in our domestic and largest international markets by transforming large geospatial datasets into actionable insights. Build a strong knowledge of available internal and external data sources. Mine and synthesize across data sources to help address opportunities leveraging geospatial data and analytic techniques. Conduct analyses to address ad hoc requests of ongoing project work. Assist in developing the machine learning (ML) and artificial intelligence (AI) components of an in-house Store Development Mapping Platform (DMAP), creating test and measurement plans and executing those plans. Continually innovate and improve upon existing methodologies and products. Consult on data collection for new products to ensure all tracking is in place for future analysis. Manipulate and analyze large, complex geospatial datasets, ensuring data quality and accessibility for advanced analytics. Work in a fast-paced, challenging environment with opportunities for skill enhancement.

Responsibilities
  • Conducts data collection, cleaning, and preprocessing to prepare datasets for analysis.
  • Develops and implements basic statistical models and machine learning algorithms to address defined business problems.
  • Collaborates with cross-functional teams to understand data requirements and deliver actionable insights.
  • Documents methodologies, processes, and results to ensure reproducibility and knowledge sharing.
  • Monitors model performance and assists in maintaining data pipelines and analytical tools.


Job Tasks
  • Extracts and transforms data from multiple sources using standard querying and scripting techniques.
  • Builds and validates predictive models using established algorithms and frameworks.
  • Generates reports and visualizations to communicate findings to stakeholders.
  • Assists in troubleshooting data quality issues and refining data collection processes.
  • Participates in code reviews and applies feedback to improve analytical solutions.


Skills
  • Proficient in data manipulation and exploratory data analysis with attention to data quality.
  • Basic understanding of machine learning concepts and ability to apply standard algorithms.
  • Effective communication skills for presenting technical information to non-technical audiences.
  • Ability to work under general supervision while managing multiple routine tasks.
  • Familiarity with version control and collaborative development practices.
  • Experience with geospatial data analysis tools, including ArcGIS (arcpy), Pandas/GeoPandas, Geospatial SQL, etc


Software Application
  • Python for data analysis and modeling.
  • SQL for data extraction and manipulation
  • Experience with ArcGIS.
  • Data visualization tools such as Tableau, Power BI, or matplotlib/seaborn libraries.
  • Jupyter Notebooks or similar integrated development environments.
  • Version control systems such as Git.
  • Experience with Fast API creation (i.e. functional programming, automated testing, performance optimization techniques)
  • Experience applying algorithms to large-scale data (e.g. supervised/unsupervised, optimization/solver)
  • Experience with Geospatial data types


Physical Requirements

Primarily sedentary work involving extended periods of computer use. Occasional requirement to attend meetings or collaborate in team environments.

Qualifications

Years Of Experience

1 to 3 years of professional experience in data science or related analytical roles.

Education

Completion of a degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, or a related discipline.

Additional Information

Benefits:
• Paid Holidays and Vacation
• Medical, Dental & Vision benefits that start on the first day of employment
• No-cost mental health support for employee and dependents
• Childcare tuition discounts
• No-cost fitness, nutrition, and wellness programs
• Fertility benefits
• Adoption assistance
• 401k matching contributions
• 15% off the purchase price of stock
• Company bonus

About Domino's

Domino's Pizza, Inc., branded as Domino's, is an American multinational pizza restaurant chain founded in 1960. The corporation is headquartered at the Domino's Farms Office Park in Ann Arbor, Michigan, and incorporated in Delaware. In February 2018, the chain became the largest pizza seller worldwide in terms of sales. Its menu features pizza, pasta, chicken wings, breadsticks, and desserts. Domino's has over 17,000 locations worldwide, including more than 11,000 in the United States. In 2020, Domino's was named the best pizza chain in the United States by the American Customer Satisfaction Index.
Learn more about Domino's
Size
13,500 employees
Market Cap
$12.5 billion
Industry
Net Income
$491.3 million
Founded
1960
5 Year Trend
+12%
Revenue
$4.1 billion
NASDAQ

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