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Data Scientist, Marketing Analytics

Job in Denver, Denver County, Colorado, 80285, USA
Listing for: Ibotta, Inc.
Full Time position
Listed on 2026-10-08
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, Data Analyst
Salary/Wage Range or Industry Benchmark: 110000 - 130000 USD Yearly USD 110000.00 130000.00 YEAR
Job Description & How to Apply Below

Ibotta is seeking a Data Scientist, Marketing Analytics to join our Publisher Insights team and contribute to our mission to Make Every Purchase Rewarding. Our team leverages the latest developments and best practices in data analyses, testing methodologies, and statistics to provide actionable insights to the Marketing Team.

As a Data Scientist, you’ll work on our Rewards Optimization models, which use uplift modeling to deliver personalized treatments in our weekly retention programs. You’ll own these models end to end, from working with stakeholders and preparing data through model development, production deployment, and ongoing monitoring. You’ll be able to advance not only your technical skills, but your organizational and leadership skills as well, by contributing to the creation of best practices for the team and company, and learning from the more senior scientists and managers on the team.

This position is located in Denver, Colorado as a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday). Candidates must live in the United States.

Not based in Denver? We will offer a relocation bonus to help make your move to the Mile High City a smooth one.

What you will be doing:
  • Build, retrain, and tune the uplift models that decide which bonus each saver receives in our weekly retention programs, balancing incremental redemptions against cost.

  • Own these models in production: maintain feature pipelines, deploy new model versions, and monitor performance and drift over time, following Ibotta’s model development standards.

  • Manage weekly model operations: review results as they come in, adjust model parameters to stay on budget, and within performance thresholds.

  • Help design and analyze the A/B tests and holdouts that measure bonus performance and produce training data for our models.

  • Report model performance and business impact to Marketing stakeholders, and explain results clearly to non-technical audiences.

  • Analyze large datasets on saver behavior to find insights that improve our models and marketing programs.

  • Work with analytics engineers, data engineers, and Marketing partners to find, define, and prepare the data needed for analysis and modeling.

  • Contribute to team best practices, including documentation, code review, and reusable modeling workflows.

  • Embrace and uphold Ibotta’s Core Values:
    Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere.

What we are looking for:
  • 2+ years of progressive experience in a professional data science, machine learning, statistics, or data analysis role, or related experience.

  • Bachelor’s degree in Computer Science, Mathematics, Statistics, Data Science, Economics or similar field required;
    Advanced degree preferred.

  • Deep Python (pandas, scikit-learn) and SQL skills. Spark or PySpark experience is a strong plus.

  • Hands-on experience building and evaluating machine learning and statistical models, such as gradient boosting and neural networks (Tensor Flow/Keras or PyTorch).

  • Working knowledge of experimentation and causal inference. Exposure to uplift or heterogeneous treatment effect modeling is a strong plus.

  • Experience deploying or maintaining at least one model in production, using Git and an orchestration tool such as Airflow or Databricks Jobs. Experience with model monitoring and drift detection is a plus.

  • Experience building features from large, event-level datasets.

  • Comfortable using AI coding assistants, and able to review, test, and debug the code they produce.

  • A passion for driving important decisions using data and data storytelling, including explaining model results and trade-offs to non-technical partners.

  • Experience with marketing incentives, promotions, loyalty, or retention programs, or with…

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