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 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 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 $1.8 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 - $175,000. 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.

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