Ibotta is seeking a Staff Data Scientist, Core Data & Analytics to join our innovative team and contribute to our mission to Make Every Purchase Rewarding. Our growing Core Data & Analytics 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. This role will be primarily focused on building data assets and analytics solutions for the revenue organization. As a Staff Data Scientist, you’ll have the unique, challenging, and rewarding opportunity to be responsible for using the latest developments in statistics and machine learning. Using these skills, you will identify and build strategic opportunities to grow the business, support initiatives, and drive value. In addition, you will be expected to build accurate and reliable Machine Learning models for use throughout the organization. You’ll be able to create and own greenfield opportunities to make big positive impacts on the revenue organization. You’ll have the chance to own the data science technology of one or more critical initiatives core business domains, from collaborating with stakeholders, through the full model development lifecycle. This position is available in multiple locations: Denver, Colorado - if you are in or willing to relocate to the Denver area, this is a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday). Remote options are available for the following states - AZ, AR, CA, FL, GA, IL, IN, IA, KS, MD, MA, MI, MN, MO, MT, NV, NJ, NY, NC, OH, OK, PA, TN, TX, UT, VA, WA, WI. If you’re not in the Denver metro area or the listed states, relocation reimbursement to Denver is available. What you will be doing: - Provide subject matter expertise and ownership of one or more foundational models involving measurement, forecasting, or optimization of our content - 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 as required - Become an expert of the Ibotta Data Ecosystem and how various teams leverage Ibotta’s suite of data to answer domain specific business questions through advanced analytic techniques - 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 knowledge, skills, and abilities. Spark/PySpark and MLOps experience is a strong plus - Excellent statistical analysis skills, with a solid understanding of experimental design About Ibotta ("I bought a...") Ibotta (NYSE: IBTA) is a leading performance marketing platform allowing brands to deliver digital promotions to over 200 million consumers through a network of publishers called the Ibotta Performance Network (IPN). The IPN allows marketers to influence what people buy, and where and how often they shop – all while paying only when their campaigns directly result in a sale. American shoppers have earned over $2.6 billion through the IPN since 2012. The largest tech IPO in history to come out of Colorado, Ibotta is headquartered in Denver, and is continually listed as a top place to work by The Denver Post and Inc. Magazine. To learn more about what our Tech teams are doing day to day, visit Building Ibotta on Medium.com. Additional Details: - This position is located in Denver, CO and includes competitive pay, flexible time off, benefits package (including medical, dental, vision), Lifestyle Spending Account, Employee Stock Purchase Program, and 401k match. Denver office perks include paid parking, snacks, and occasional meals. - Base compensation range: $152,000 - $203,000. Total compensation for this role also includes a variable component in addition to base salary. Equity is included in overall compensation package. This compensation range is specific to the United States labor market and may be adjusted based on actual experience. - 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. #LI-Remote #BI-Remote #BI-Hybrid

• Design, implement, and maintain robust data pipelines, from event generation through ETL to clean, intelligent storage. • Retrieve, process, and integrate data using APIs and webhooks, ensuring quality, accuracy, and integrity at every step. • Develop reporting layers—dashboards, automated reports, and notifications—to deliver insights across teams. • Curate raw data into meaningful structures for CRM, product, and monetization teams. • Build predictive and optimization models for areas like player lifetime value, churn prediction, monetization strategies, and game recommendations. • Define and execute multivariate testing frameworks to optimize product and campaign performance. • Explore and apply state-of-the-art AI and ML techniques, in real-time processes, proposing innovative approaches for real-world challenges. • Partner and influence cross-functional teams—including CRM, Server, Data Engineering, and Leadership—to implement end-to-end solutions quickly and effectively. • Align data projects with business goals and ROI considerations, applying pragmatic 80/20 thinking to maximize impact. • Deeply understand and navigate the abstract mechanics of our ecosystem—game economies, monetization levers, RTPs, and more.

Role Description We are looking for a detail-obsessed Applied Data Scientist to join our growing team. The ideal candidate is passionate about the foundational layer of all data analysis: ensuring our data is clean, accurate, and reliable. You are a detective at heart, driven by a deep curiosity to understand complex data systems, and someone who finds immense satisfaction in transforming messy, ambiguous datasets into pristine assets that drive critical business decisions. This role is perfect for a scientist who wants to own the entire journey: from taking raw application data to generating clean inputs, to building models and delivering tangible value in real-world applications. You will be a central point of contact, communicating with engineers, product managers, and business analysts to ensure data integrity from collection to analysis. How you will make an impact - Model Ownership: Participate in the full modeling lifecycle, from statistical analysis and experimentation to building, validating, and iterating on machine learning models that address critical business challenges. - Data Quality: Own the data foundation by preparing, cleaning and transforming raw, complex data into high-quality features for modeling. Proactively identify and handle missing values, outliers, and inconsistencies. - Problem Investigation: Investigate data discrepancies (tracking bugs, ETL errors, definitional issues) and design automated frameworks to ensure data accuracy. - Cross-Functional Collaboration: Act as a strategic liaison, collaborating with data Engineering and product teams to drive the data strategy and definition of our centralized feature store, ensuring it becomes the 'single source of truth' for all ML models. - Documentation: Create and maintain clear, authoritative documentation for data sources, cleaning processes, and variable definitions. Qualifications - Obsessed with Details: You have an exceptional eye for detail and a low tolerance for errors. You believe that accuracy and precision are non-negotiable. - A Strategic Thinker: You can see the bigger picture and are passionate about building robust systems and processes that will stand the test of time. - Proactive & Persistent: You don't wait for problems to find you. You actively seek out data quality issues and are persistent in seeing an investigation through to its resolution. - Curious & Adaptive: You are inherently curious and possess a strong desire to understand how things work. You're comfortable with ambiguity and skilled at breaking down complex problems. Requirements - Education: Bachelor’s degree (PhD preferred) in a quantitative field (Statistics, Physics, Mathematics, etc.). - Programming: Strong proficiency in Python (Pandas/NumPy) and SQL for complex querying and data manipulation. - Data Quality: Hands-on experience with data cleaning techniques and data validation frameworks. - Tooling: Familiarity with data visualization tools to help identify and communicate data issues. Benefits - Comprehensive benefits package including health, dental, and vision coverage. - Paid time off and paid parental leave. - 401(K) plan with employer matching. - Wellness benefits, among others. - Equity opportunities may also be part of your total rewards package.

• Build and iterate on predictive models that move us from ranges (e.g. '3–5 days') to accurate, specific delivery dates • Incorporate hub performance data, team throughput, and routing logic to continuously improve prediction accuracy • Develop and own demand forecasting models for Express offerings across diamonds, melee, gemstones, and jewellery • Determine optimal inventory levels by hub and product type to meet demand without overstocking • Identify opportunities to reduce lead times and improve fulfilment accuracy across the network • Partner closely with data engineering team to define data requirements and build robust pipelines • Surface actionable insights to the Fulfilment org to drive speed and accuracy — two of the company's three core pillars (quality, speed, price)