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Salary: USD 144,000 - 165,000 / annual
Ibotta, a leading performance marketing platform (NYSE: IBTA), is seeking a Senior Data Scientist to join the Client Data & Measurement team. The role focuses on creating data and analytical solutions across the business, with a mission to understand customer behavior and provide recommendations that drive business growth.
You will be responsible for leveraging statistics, machine learning, and data visualization to identify and build strategic opportunities. Key responsibilities include:
- Collaborating with stakeholders, architects, and data engineers to discover, define, cleanse, and refine datasets for analysis and modeling
- Building strong cross-departmental relationships to understand business problems and improvement opportunities
- Analyzing and building large, novel datasets to extract actionable insights for model development and understanding customer behavior and product performance
- Prioritizing projects based on business impact and managing large-scale initiatives
- Developing models using statistical and machine learning techniques, optimizing performance across various approaches
- Becoming an expert in Ibotta's data ecosystem and how teams leverage data to answer domain-specific questions
- Informing experimental design to address major business challenges and innovation opportunities
- Providing data science mentoring and education to the team and across the company
The position is hybrid, requiring 3 days in office (Tuesday, Wednesday, Thursday) in Denver. Relocation assistance is available for candidates outside the Denver area.
REQUIREMENTS:
- 5+ years of professional experience in data science or machine learning roles with significant impact
- Bachelor's degree in Computer Science, Engineering, Analytics, or related field
- Demonstrated passion for driving important decisions using data and data storytelling
- Expert-level Python knowledge and skills; Spark or PySpark experience is a strong plus
- Applied experience with machine learning and statistical algorithms to optimize processes, predict outcomes, and forecast trends
- Excellent statistical analysis skills; understanding of experimental design and time series analysis is a strong plus
- Expert-level knowledge in database manipulation, query languages, and graph data schemas
- Experience manipulating complex data for feature engineering within data lakes, distributed systems, and data streams
- MLOps experience is a strong plus but not required
- History of continuous learning and staying current with data science advances; community contributions (conference presentations, publications, recognized internet presence) are a strong plus
- Superior analytical and problem-solving skills
