Company Description
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.
Job Description
This position requires an individual with a combination of computational and analytical skills. The candidate should have a solid foundation in computer science and statistics/math with well-honed skills in the following areas:

• Data Management
  • experience with both structured and unstructured data, and Hadoop or similar technologies
  • able to identify, join, explore and examine data from multiple disparate sources and formats
  • ability to reduce large quantities of unstructured or formless data and get it into a form in which it can be analyzed
  • ability to deal with data imperfections such as missing values, outliers, inconsistent formatting, etc.
• Statistics & Modeling
  • knowledge of statistical theories and techniques commonly used in prediction and optimization models
  • ability and desire to go beneath the surface of a problem and distill it into a clear set of hypotheses that can be tested
  • Design, plan, and manage projects from start to finish & produce data-driven results with appropriate techniques to answer key business questions
  • mastery of statistical programming languages such as R and Python
• Machine Learning
  • experience with machine learning algorithms, such as k-nearest neighbors, random forests and ensemble methods and their corresponding implementation packages in R or Python
  • understand when it is appropriate to use different techniques
  • experience with distributed computing, such as Hadoop, Spark or related technologies
• Software Development
  • the ability to write code in programming languages such as SAS, Java, R, and Python
  • capable of developing prototypes and fashion their own tools to conduct analytic research

Qualifications

• Advanced degree (Master's/PhD) in Statistics, Computer Science or other quantitative discipline
• Minimum of 5 years of related experience
• Mastery of various statistical methodologies such as regression analysis (linear and non-linear), cluster analysis, CHAID, time series, survival models
• Experience with machine learning
• Experience with SQL, Scala, Python or Java
• Proficiency in at least one open source statistical program like R and KNime
• Working knowledge of Hadoop and other big data technologies
• Strong understanding of Statistics and modeling techniques
• Strong analytic thought process and ability to interpret findings
• Ability to work on multiple assignments concurrently

In addition, the candidate should have strong business acumen, and interpersonal and communication skills, yet also be able to work independently. He/she should be able to communicate findings and the way techniques work in a manner that all stakeholders, both technical and non-technical, will understand.
Project oriented workload:

• Marketing Objective: Defining the marketing goal and its application
• Data: Specification of the dependent variable, its interactions will all data sources. Performing data cleansing, exploratory data analysis and development of a self-contained code to capture all summarization, including missing values, left and right outliers and data dictionaries
• Feature Engineering: Being able to develop new variables among different dimensions and mathematical transformations
• Modeling: Develop a consistent variable selection. Ability to work across different algorithms and techniques. Ability to fine-tuning parameters. Identification of champion and challengers' models. Criteria to identify final model and refining it to achieve final solution
• Deployment & Implementation: Ability to implement API from the scoring algorithm, back testing and produce the proper documentation

Qualifications
Additional Information
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.
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