Responsibilities

• 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.

Requirements

• 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 (TensorFlow/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 плюс.
• 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.

Preferred

• Exposure to uplift or heterogeneous treatment effect modeling is a strong plus.
• Experience with marketing incentives, promotions, loyalty, or retention programs, or with models that balance competing goals such as volume and cost, is a plus.

Benefits

• competitive pay, flexible time off, benefits package (including medical, dental, vision), Employee Stock Purchase Program, and 401k match.
• Denver office perks include paid parking, snacks, and occasional meals.