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 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. Not based in Denver? We will offer a relocation bonus to help make your move to the Mile High City a smooth one. 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 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. - 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: $152,000 - $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. #LI-Remote #BI-Remote #BI-Hybrid

• Design, develop and deploy advanced statistical or machine learning models related to credit risk, pricing, collections, fraud, and other high-impact business use cases that drive better data-driven decisions • Execute the full model lifecycle, from initial data discovery and feature engineering to deployment, monitoring and iterative improvement • Partner with cross-functional teams including Portfolio Strategy, Collections, Engineering, Product, Underwriting, and Sales to integrate models into our applications and ensure they function seamlessly • Communicate complex technical concepts, model results, and business implications to both technical and non-technical stakeholders • Develop production-grade code and contribute to internal toolkits, documentation, and peer code review to ensure high-quality delivery • Build and maintain production machine learning pipelines and monitoring systems to ensure models are reliable, scalable and continuously improving

• Dive into various clinical and coding audits, unpacking the data that drives audit decisions, and understanding past outcomes. • Curate labeled data, hypothesize new features, and develop ML models that target claims for audit with even greater precision. • Measure model performance rigorously, translating outcomes into operational insights and recommendations for our clients. • Work with vast, nuanced data pipelines derived from intricate business workflows—often unclean and undefined—to refine them for robust modeling. • Enhance data pipelines, modeling infrastructure, and team tools to level up our capabilities and decision-making efficiency. • Build expertise in healthcare data and make an impact on the industry. Engage with clients and internal experts to refine model insights, ensuring alignment with real business needs.

• Design, develop, and optimize supervised, unsupervised, and reinforcement learning models. • Implement and fine-tune deep learning architectures using frameworks such as TensorFlow and PyTorch. • Apply ethical AI principles, including fairness, transparency, privacy, and bias mitigation. • Deploy and monitor models in production environments, ensuring scalability and reliability. • Build and maintain scalable data pipelines and ETL processes for real-time and batch analytics. • Engineer robust data architectures using Spark, MetaFlow, Databricks, and cloud platforms (Azure, AWS, GCP).