Senior Manager, Product Analytics
Ibotta is seeking a Senior Manager, Product Analytics to join our innovative team and contribute to our mission to Make Every Purchase Rewarding. Leading a decision science team, you'll champion data-driven decisions across the product lifecycle as a cross-functional leader for our Consumer & Client Experience Groups. You and your team will inform product strategy, prove out data science use cases within Product Analytics, and leverage our full analytics stack (Databricks, Spark, Airflow, GitHub, Python, Looker, etc) to mine insights from rich behavioral and transactional data sources for a large base of consumers across thousands of brands.
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:
Empower and partner with product leaders to use our rich historical data to define, prioritize and measure high-impact initiatives
Proactively contribute to product strategy by ideating, surfacing and developing strategic initiatives for growth, optimization and reduction of friction across the user experience
Drive a culture of measurement by championing and teaching best practices in KPI development, measurement frameworks and statistical modeling
Lead the team to conduct deep dives on product features, flows, funnels and user journeys to identify actionable recommendations and testable hypotheses
Use modeling and data mining to generate deep insights, user segmentations, predictions, and functionality answering complex strategic questions that drive broader innovation
Ensure the team designs, executes and analyzes A/B tests with statistical integrity that have clear learning agendas, evaluation criteria and guardrails
Design, deliver and present compelling data visualizations and insights that effectively communicate recommendations to and generate buy-in from leadership and cross-functional stakeholders.
Own the design, implementation, governance and monitoring of tracking events across our digital properties
Increase time-to-insight by automating repeatable workflows, analyses and processes and enabling self service analytics by creating reusable data and reporting assets
Lead the build-out of data science capabilities within the Product Analytics team, partnering with ML Product engineers to prototype, test, and productionize models
Own large, complex analytics projects end-to-end in a fast-paced environment that focus on business impact and support the strategic goals of the product organization
Embrace and uphold Ibotta’s Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere
What we are looking for:
8+ years of practical work experience in analytics and data science; experience working in consumer product development teams strongly preferred
4+ years of leading analytics teams
Bachelor's degree in Computer Science, Mathematics, Statistics, Data Science, Economics or similar field required (advanced degree preferred)
Expertise working with:
Data analysis tools (e.g., Databricks, SQL, Python/R, Spark, Hive, Airflow, Git/GitHub etc.)
BI & other analytics tools (e.g., Looker, GA, Amplitude, etc.)
Data pipelines and ETL/ELT processes
Proven track record of success leading data-driven product decisions and outcomes in cross-functional product teams at consumer-focused tech companies.
Deep subject matter expertise in statistical measurement techniques (causal inference, A/B testing, diff-in-diff estimation, etc) with the ability to coach individual team members
Knowledge and application of statistical modeling techniques (regularized regression, time series, tree-based models, clustering, etc.) and development of analytical tools to deliver measurable product outcomes
Experience leading analytics and data science projects end-to-end, including data cleaning, model development/evaluation/deployment, and communication of value.
Clear communications skills that bridge the gap between technical and non-technical audiences, break ambiguous business questions into structured analysis, and translate complex data into actionable insights.
Experience building centralized and extensible code repositories, packages, and workflows in Python and interest in MLOps a big plus