Full-Time

Senior Data Scientist

Fraud Analytics

Confirmed live in the last 24 hours

ibotta

ibotta

501-1,000 employees

Shopping rewards app for cash-back offers

Consumer Software
Consumer Goods

Compensation Overview

$128k - $145kAnnually

Senior

Denver, CO, USA

Hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday).

Category
Data Science
Data & Analytics
Required Skills
Python
Data Science
Tensorflow
R
Pytorch
Apache Spark
SQL
AWS
Splunk
Databricks
Requirements
  • 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
  • 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
Responsibilities
  • 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

Ibotta operates a shopping rewards app that connects brands with millennial consumers by offering cash-back rewards for purchases. Users earn cash back by shopping at partner retailers, which encourages them to shop more frequently and spend more per visit. Brands and retailers collaborate with Ibotta to promote their products through targeted advertising within the app, especially during major shopping events like Black Friday. Ibotta generates revenue by charging brands for featured placements and marketing campaigns designed to increase sales velocity and conversion rates. The company differentiates itself by providing valuable insights and tools that help brands understand consumer behavior, making it easier for them to reach their target audience effectively. Ibotta's goal is to enhance brand awareness and drive incremental sales for its partners while providing a rewarding shopping experience for consumers.

Company Stage

IPO

Total Funding

$58.4M

Headquarters

Denver, Colorado

Founded

2012

Growth & Insights
Headcount

6 month growth

1%

1 year growth

3%

2 year growth

10%
Simplify Jobs

Simplify's Take

What believers are saying

  • Ibotta's successful IPO and strong market capitalization of $3.1 billion indicate robust financial health and growth potential.
  • The company's innovative marketing strategies, such as the 'Make It Rain' experiential campaign, demonstrate a commitment to creative consumer engagement.
  • Partnerships with major retailers like Walmart and Schnucks enhance Ibotta's market reach and credibility.

What critics are saying

  • The competitive landscape of the shopping rewards market could pressure Ibotta to continuously innovate to maintain its edge.
  • Dependence on partnerships with major retailers means that any disruption in these relationships could significantly impact Ibotta's business.

What makes ibotta unique

  • Ibotta's focus on millennial consumers and cash-back rewards sets it apart from traditional loyalty programs that may not resonate as strongly with this demographic.
  • The company's ability to drive incremental sales through targeted marketing campaigns provides a measurable ROI for brands and retailers, unlike more generic advertising platforms.
  • Ibotta's partnerships with major retailers like Walmart and its innovative experiential campaigns highlight its commitment to engaging consumers in unique and memorable ways.

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Benefits

Parental leave

Onsite gym

Dinner perk

Healthcare coverage

Culture club

401(k) match

Team wide bonus

Flexible time off

Equity

Lifestyle spending account