SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 110,000 - 130,000 / annual
Ibotta, a leading performance marketing platform (NYSE: IBTA), is seeking a Data Scientist for its Publisher Insights team to support marketing analytics and rewards optimization. The role focuses on building and maintaining uplift models that personalize bonus treatments in weekly retention programs, balancing incremental redemptions against cost.
Key responsibilities include:
- Build, retrain, and tune uplift models that determine bonus allocation for savers in weekly retention programs
- Own models end-to-end in production: maintain feature pipelines, deploy new versions, monitor performance and drift
- Manage weekly model operations: review results, adjust parameters to stay on budget and within performance thresholds
- Design and analyze A/B tests and holdouts to measure bonus performance and generate training data
- Report model performance and business impact to Marketing stakeholders, translating results for non-technical audiences
- Analyze large datasets on saver behavior to identify insights that improve models and marketing programs
- Collaborate with analytics engineers, data engineers, and Marketing partners to identify, define, and prepare data
- Contribute to team best practices through documentation, code review, and reusable modeling workflows
This is a hybrid position based in Denver, Colorado, requiring 3 days in office (Tuesday, Wednesday, Thursday). Relocation assistance is available for candidates outside Denver. The role offers competitive pay, flexible time off, comprehensive benefits (medical, dental, vision), ESPP, 401k match, and office perks including paid parking and snacks.
Requirements:
- 2+ years of progressive experience in data science, machine learning, statistics, or data analysis (or related field)
- Bachelor's degree in Computer Science, Mathematics, Statistics, Data Science, Economics, or similar field (advanced degree preferred)
- Deep proficiency in Python (pandas, scikit-learn) and SQL; Spark/PySpark experience is a strong plus
- Hands-on experience building and evaluating ML and statistical models (gradient boosting, neural networks with TensorFlow/Keras or PyTorch)
- Working knowledge of experimentation and causal inference; uplift or heterogeneous treatment effect modeling experience is a strong plus
- Experience deploying or maintaining at least one model in production using Git and orchestration tools (Airflow or Databricks Jobs); model monitoring and drift detection experience is a plus
- Experience building features from large, event-level datasets
- Comfortable using AI coding assistants and able to review, test, and debug generated code
- Passion for data-driven decision making and data storytelling, including explaining model results and trade-offs to non-technical partners
- Experience with marketing incentives, promotions, loyalty, retention programs, or models balancing competing goals (volume vs. cost) is a plus
- Must be currently authorized to work in the United States on a full-time basis
