Machine Learning Manager, Recommendations & Personalizations at Ibotta
Ibotta is seeking a Machine Learning Manager with expertise in recommendation and personalization systems to help drive our company’s mission to make every purchase rewarding for millions of consumers. We are looking for a self-motivated manager who has a passion for pushing the envelope with scalable machine learning solutions leveraging cutting-edge cloud technology. The ideal candidate will be an experienced, collaborative and inspiring leader with a track record of attracting, recruiting, developing and retaining world-class talent.
What you will be doing:
- Embrace and uphold Ibotta’s Core Values: Integrity, Boldness, Outhustle, Teamwork, Transparency & A good idea can come from anywhere
- Lead the team responsible for designing, developing and deploying large scale, big data-driven recommendation and personalization models that are integrated across the Ibotta ecosystem
- Mentor the talented individual contributors on your team to grow and develop their professional and technical skills
- Collaborate with product management, engineering, and analytics leadership to help identify high impact applications for machine learning and data science solutions
- Communicate complex solutions, concepts and the results in a clear and concise manner to business stakeholders
- Champion a data-driven culture and drive business value through the creation and adoption of machine learning initiatives
- Research industry trends and standards to stay abreast of new developments and continue to push the envelope on machine learning solutions at Ibotta
What we are looking for:
- 5+ years of professional experience as a Machine Learning Engineer, Data Scientist, or equivalent role with 2+ years in a tech lead and/or team management role
- 2+ years of professional experience building and deploying recommendation and personalization systems
- Strong track record of developing, motivating and inspiring individual contributors
- Extensive knowledge of advanced Machine Learning techniques concerning ranking, recommendations and personalization
- Experience working with machine learning frameworks (e.g. scikit-learn, xgboost, PyTorch, TensorFlow) and distributed big-data tools (Spark, Hive)
- Hands-on experience operationalizing machine learning models (ensuring best practices and frameworks around testing, monitoring, reliability, security, etc.)
- Excellent interpersonal and communication skills with the proven ability to collaborate across functional areas to translate high-level business objectives into tangible data science solutions, establish priorities and drive towards common goals
- Experience with AWS is strongly preferred
Built in Denver, CO, Ibotta ("I bought a...") is a free mobile shopping app that gives users cash back on groceries and more. Through our partnerships with brands and retailers like Procter & Gamble, Kraft Heinz, Kellogg, Amazon, Walmart, Target and Uber, we’ve delivered over $750 million in cumulative cash rewards to our Savers. Guided by our values and our mission to make every purchase rewarding, we come to work energized by the business problems we get to solve, the technology we get to build, and the people we get to innovate (and have fun) with. Ibotta made Inc.’s 2020 list of the 5000 fastest-growing private companies in the U.S. for the third consecutive year. In 2019, we became the first mobile consumer technology company in Colorado to achieve $1B in valuation.
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, benefits package (including medical, dental, vision), 401k, and equity.
- Ibotta provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, and genetics.
- Applicants must be currently authorized to work in the United States on a full-time basis.
- 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.