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Ibotta

Data Scientist, Marketing Analytics

Ibotta

. Build, retrain, and tune uplift models that determine which bonus each saver receives in weekly retention programs .

Posted 10/5/2026full-timeDenver • Colorado • United StatesJuniorMid-Level💰 $110,000 - $130,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in building, deploying, and maintaining machine learning models, with a strong focus on data analysis and performance monitoring. Proficient in Python, SQL, and model evaluation techniques, with the ability to communicate complex results to non-technical stakeholders.

Highest-signal resume keywords
Machine Learning Model DevelopmentPython (Pandas, Scikit-Learn)SQL ProficiencyModel Deployment (Git, Airflow, Databricks)A/B Testing and Causal Inference

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Machine LearningStatistical ModelingData AnalysisFeature EngineeringModel MonitoringGradient BoostingNeural Networks (TensorFlow/Keras, PyTorch)Uplift ModelingData StorytellingDebugging
Soft Skills
CommunicationCollaborationProblem-SolvingAdaptabilityAttention to Detail
Tools & Technologies
GitAirflowDatabricksSparkPySpark
Industry Keywords
Data ScienceMachine LearningMarketing IncentivesRetention ProgramsCausal Inference

Tech Stack

Tools & technologies
AirflowKerasPandasPySparkPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

Key responsibilities & impact
  • Build, retrain, and tune uplift models that determine which bonus each saver receives in weekly retention programs
  • Own models in production, including maintaining feature pipelines, deploying new model versions, and monitoring performance and drift
  • Manage weekly model operations, review results, adjust model parameters, and maintain budget and performance thresholds
  • Help design and analyze A/B tests and holdouts measuring bonus performance and producing training data
  • Report model performance and business impact to Marketing stakeholders
  • Explain results clearly to non-technical audiences
  • Analyze large datasets on saver behavior to improve models and marketing programs
  • Work with analytics engineers, data engineers, and Marketing partners to define and prepare data for analysis and modeling
  • Contribute to team best practices, documentation, code review, and reusable modeling workflows
  • Uphold Ibotta’s Core Values
  • Securely handle data, identify and report phishing attempts, and report security incidents

Requirements

What you’ll need
  • 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 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
  • 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 models that balance competing goals such as volume and cost, is a plus
  • Candidates must live in the United States
  • Applicants must be currently authorized to work in the United States on a full-time basis

Benefits

Comp & perks
  • Flexible time off
  • Medical insurance
  • Dental insurance
  • Vision insurance
  • Employee Stock Purchase Program
  • 401k match
  • Paid parking
  • Snacks
  • Occasional meals
  • Variable compensation component in addition to base salary
  • Equity included in overall compensation package