Ibotta

Decision Scientist

Hybrid - Denver · Full-time

Work authorization required$89k-$101kDetected 42 days ago

PythonGitSQLData AnalysisData EngineeringData ScienceData VisualizationStatisticsMarketing AnalyticsPerformance MarketingLeadershipProblem Solving

About the role

Our relatively new and fast-growing Client Analytics team provides high-quality, on-time data products and services across all business areas within Ibotta.
We do this through our thought leadership, subject matter expertise, evangelism, and governance of business-critical data initiatives.
In addition, you'll also be able to grow organizational and leadership skills by contributing to team and company best practices while learning from technology leaders who want you to be successful.

Support projects to derive inference and insights from our measurement models, provide ad hoc analysis to internal and external stakeholder using ibotta's data that tie back to clients goals and objectives for their business, automation of existing reports and deliverables,and market analysis case studies
Collaborate with business stakeholders and clients to provide insightful reporting and dashboards
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).
To learn more about what our Tech teams are doing day to day, visit Building Ibotta on https://medium.com/building-ibottaMedium.com http://Medium.com.
As a Decision Scientist, you'll have the challenging and rewarding opportunity to build on the foundation of already established data and analytics products.
You'll be able to drive initiatives forward, being responsible for project completion.

3+ years practical work experience in an analytics role
Bachelor's degree in analytics/mathematics/statistics/data science/computer science/economics
Proven expertise with data handling, processing, statistical and analytical skills
Ability to think creatively and provide thoughtful, agile insights
In-depth experience with SQL required

Experience with modern BI tools (e.g., Looker, Tableau)
Experience with Git/GitHub
Experience with data pipelines and ETL/ELT processes
Experience using modern data analysis tools (such as R, Python, Hive/Presto, Pyspark) preferred
CPG / marketing analytics experience is preferred but not required

are comfortable continually asking questions of our data and business
translate measurement outcomes into technical specifications and ambiguous business questions into structured data problems
use solid business sense to tie analytical outputs to actionable recommendations
analyze, visualize, communicate and automate complex learnings, distilling them into digestible form for a broad set of stakeholders

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.
Applicants must be currently authorized to work in the United States on a full-time basis.
Applicants are accepted until the position is filled.
$89,000 - $101,000.
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.

We will offer a relocation bonus to help make your move to the Mile High City a smooth one.
This position is located in Denver, CO and includes competitive pay, flexible time off, benefits package (including medical, dental, vision), Employee Stock Purchase Program, and 401k match.
Denver office perks include paid parking, snacks and occasional meals.

Ibotta is seeking a Decision Scientist, Client Analytics to join our high-performing team and contribute to our mission to Make Every Purchase Rewarding.

Applicants must be currently authorized to work in the United States on a full-time basis.

This listing is sourced directly from Ibotta's careers page and normalized into a canonical job model.