Staff Data Scientist, Client Data & Measurement
Ibotta — Apps · Commerce and Shopping · Coupons
About the role
Ibotta is seeking a Staff Data Scientist, Client Data & Measurement to join our innovative team and contribute to our mission to Make Every Purchase Rewarding. Our newly formed and growing Core Data Science Team provides high-quality, on-time data science-related products and services across all business areas and teams within Ibotta. We do this by providing thought leadership, subject matter expertise, evangelism and governance of business-critical data science initiatives.
As a Staff Data Scientist, you’ll have the unique, challenging, and rewarding opportunity to build the foundation of data and data science within the company. You’ll be able to create and own greenfield opportunities to make big positive impacts on the business across several teams and business areas. You’ll have the chance to own the data science technology of one or more important core business domains, from collaborating with stakeholders, through the full model development lifecycle. You’ll be able to advance not only your technical skills, but your organizational and leadership skills as well, by establishing and leading best practices for the team and company, and providing mentoring and education across the company.
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.
What you will be doing:
- Provide subject matter expertise and ownership of one or more of the company’s core business domains
- Establish and lead best practices, setting the example for the team
- Initiate and drive collaboration with stakeholders, architects, and data engineers to discover, define, cleanse, and refine the data needed for analysis and modeling
- Analyze large and novel datasets to extract actionable insights to inform model development and understand consumer behavior
- Provide customized views of large and complex datasets to support data analysis and business decision-making
- Inform experimental design to formulate solutions addressing major business challenges and innovation opportunities
- Build models using a variety of statistical and machine learning techniques, from selecting the best type of model for the problem to using advanced techniques to measure and optimize model performance
- Harden data pipelines and models for production deployment and monitoring of performance over time
- Provide mentoring and education to this team and other teams across the company
- Embrace and uphold Ibotta’s Core Values of Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere
What we are looking for:
- 7+ years of experience making significant positive impacts in a professional data science or machine learning role
- Bachelor’s degree in Computer Science, Engineering, Analytics or a related field required
- A history of and passion for driving important decisions using data and data storytelling
- A love of learning and continuous development, including staying at the forefront of the latest advances in data science and machine learning. Broad-scale community contributions to the fields of data science and machine learning in the way of conference presentations, professional publications, and/or recognized internet presence are a strong plus
- Expert-level knowledge, skills, and abilities in creating, developing, and applying a variety of new or existing machine learning and statistical algorithms
- Expert-level Python and/or R knowledge, skills, and abilities. Spark or PySpark experience is a strong plus
- Excellent statistical analysis skills, with a solid understanding of experimental design and time series analysis a strong plus
- Superior analytical and problem solving skills
- Expert-level knowledge, skills, and abilities in database manipulation, query languages, and graph data schemas
- Experience manipulating complex data to apply business rules for improved feature engineering within data lakes, distributed systems, and data streams
- Experience in MLOps a strong plus
Additional Details:
- This position is located in Denver, CO and includes competitive pay, flexible time off, benefits package (including medical, dental, vision), Employee Stock Purchase Program, and 401k match. Denver office perks include paid parking, bagel Wednesdays, snacks and occasional meals.
- Base compensation range: $180,000 - $203,000. This compensation range is specific to the United States labor market and may be adjusted based on actual experience. Total compensation for this role also includes a variable component in addition to base salary.
- Ibotta is an Equal Opportunity Employer. Ibotta’s employment decisions are made without regard of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected status.
- Applicants must be currently authorized to work in the United States on a full-time basis.
- Applicants are accepted until the position is filled.
- For the security of our employees and the business, all employees are responsible for the secure handling of data in accordance with our security policies, identifying and reporting phishing attempts, as well as reporting security incidents to the proper channels.
What the index says about this role
- First seen by JobLarper — Aug 4, 2026, 4 days ago. Older postings collect hundreds of applicants — a tailored résumé matters more the longer a role has been live.
- No pay range in our index for this listing. Across 89 indexed Data Scientist roles in US that do publish one, the middle half sits between $195k and $308k, median $240k — JobLarper's read of the market, not a figure from Ibotta.
- What Data Scientist roles ask for — across 355 indexed openings: Python (76%), SQL (63%), ML (58%), REST/APIs (34%), AI/LLM (30%). This posting names Python, ML.
- Ibotta is hiring actively — 6 open roles indexed.
Derived from the 27,000 roles JobLarper indexes daily from official company boards — not from the job description above.
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