Epsilon is the leader in outcome-based marketing. We enable marketing that’s built on proof, not promises. Through Epsilon PeopleCloud, the marketing platform for personalizing consumer journeys with performance transparency, Epsilon helps marketers anticipate, activate and prove measurable business outcomes. Powered by CORE ID®, the most accurate and stable identity management platform representing 200+ million people, Epsilon’s award-winning data and technology is rooted in privacy by design and underpinned by powerful AI. With more than 50 years of experience in personalization and performance working with the world’s top brands, agencies and publishers, Epsilon is a trusted partner leading CRM, digital media, loyalty and email programs. Positioned at the core of Publicis Groupe, Epsilon is a global company with over 8,000 employees in over 40 offices around the world. For more information, visit epsilon.com. Follow us on Twitter at @EpsilonMktg.
As a Data Scientist in our Decision Sciences R&D organization, you will be responsible for researching and building machine learning, natural language processing, and recommender system applications to extend Epsilon’s CORE Personalization Platform. Epsilon’s CORE Personalization Platform analyzes anonymized data at internet scale and evaluates more than one trillion advertising opportunities per month in real-time. You will work on real-world problems as part of our highly collaborative Decision Sciences Research & Development team, and your data science and AI solutions will directly and rapidly impact our business. This includes analyzing raw source data and derived data, researching and developing models, algorithms, and applications, building tools and analyses for new and existing products as well as presenting findings.
- Develop an understanding of Epsilon’s CORE Personalization Platform and proprietary datasets
- Use your machine learning expertise to research and recommend the best approaches to solving our technology and business problems
- Design, implement, and validate your solutions in Apache Spark and Apache Hive, using Scala or Python on large, state-of-the-art computing clusters
- Work with our Engineering teams to integrate your solutions into Epsilon’s CORE Personalization Platform
- Participate fully in our collaborative approach to research and applications projects
- A Ph.D. in Computer Science, Statistics, Linguistics, Electrical Engineering, Mathematics, Economics, Physics, Operations Research, or a related scientific discipline
- Research experience and coursework in Machine Learning
- Fluency in programming such as Python, SQL, Scala and/or Java
- Familiarity with distributed computing, such as Hadoop, Spark, or related technologies
- Experience with large data sets
- Strong understanding of modeling and statistical techniques
- Desire to work in a highly collaborative environment
Additional, But Not Required Skills
- Experience with Recommender Systems, Natural Language Processing, Information Retrieval, Mathematical Optimization, Control Theory, Time-Series Analysis, or Causal Inference
Great People, Deserve Great Benefits
We know that we have some of the brightest and most talented associates in the world, and we believe in rewarding them accordingly. If you work here, expect competitive pay, comprehensive health coverage, and endless opportunities to advance your career.
Epsilon is an Equal Opportunity Employer. Epsilon’s policy is not to discriminate against any applicant or employee based on actual or perceived race, age, sex or gender (including pregnancy), marital status, national origin, ancestry, citizenship status, mental or physical disability, religion, creed, color, sexual orientation, gender identity or expression (including transgender status), veteran status, genetic information, or any other characteristic protected by applicable federal, state or local law. Epsilon also prohibits harassment of applicants and employees based on any of these protected categories.
Epsilon will provide accommodations to applicants needing accommodations to complete the application process.