Initiate and drive collaboration with stakeholders, architects, and data engineers to discover, define, cleanse, and refine the data needed for analysis and modeling
Consult on fraud risk mitigation for new cross-functional initiatives and provide recommendations and action plans for mitigating risk to discover, define, cleanse, and refine the data needed for analysis
Establish meaningful cross departmental relationships with stakeholders and peers to understand business problems and opportunities for improvements
Analyze, and at times build, large and novel datasets to extract actionable insights to inform model development and understand customer behavior and areas of fraud risk
Ability to prioritize projects based on business impact and value; lead and manage large scale projects
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 for identifying, monitoring, and actioning on fraud trends
Become an expert of the Ibotta Data Ecosystem and how various team’s leverage Ibotta’s suite of data to answer domain specific business questions through advanced analytic techniques
Inform experimental design to formulate solutions addressing major business challenges and innovation opportunities
Provide data science mentoring and education to this team and others across the company, and contribute to creating best practices for the team
Embrace and uphold Ibotta’s Core Values of Integrity, Boldness, Ownership, Teamwork, Transparency, & Advocate for Savers to help Make Every Purchase Rewarding
5+ years of experience making significant impacts in a professional data science or machine learning role
Bachelor’s degree in Computer Science, Statistics, Data Science or similar field required; Advanced degree preferred
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, with specific experience using binary classification, dealing with unbalanced datasets, and fraud or fraud-related modeling experience using tools such as XGBoost, Tensorflow, Pytorch, LLMs
Expert-level experience using modern data analysis tools and languages (SQL, Python, R, Spark or PySpark, Databricks, Imply, AWS, Splunk, etc.)
Advanced 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
Excellent statistical analysis skills, with a solid understanding of experimental design is a strong plus
Experience with and knowledge of software engineering principles and how to apply those skills to data science (e.g. knowing how to build a model but also having an understanding of how to manage and deploy that model) is a strong plus
Experience with image recognition tools and software is a plus
Superior analytical and problem solving skills
This position is located in Denver, CO and includes competitive pay, flexible time off, benefits package (including medical, dental, vision), Lifestyle Spending Account, and 401k match. Denver office perks include paid parking, bagel Thursdays, snacks and occasional meals.
Base compensation range: $128,000 - $145,000. Equity is included in the 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.
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.