Associate Director, Decision Sciences

  • 6021 Connection Dr, Irving, TX 75039, USA
  • Full-time

Company Description

Positioned at Publicis Groupe's core, Epsilon is a leader in interaction management, empowering brands to transform ordinary customer experiences into meaningful, human experiences. Through a connected suite of products and services, Epsilon combines leading-edge identity management, industrial strength data and technology expertise with big brand acumen gained over five decades working with the industry’s top brands. Our human-powered, data-led marketing delivers unmatched depth, breadth and scale to help brands turn meaningful human interactions into exceptional business outcomes.

Job Description

Company:        Epsilon Data Management LLC


Job Title:           Assoc Dir, Decision Science, multiple positions, various levels


Job Code:         #6630.4664


Job Location:   6021 Connection Drive, Irving, TX 75039 and various, unanticipated sites throughout the U.S.


Job Type:          Full Time


Duties:  Formulate and apply mathematical modeling and other optimizing methods to develop and interpret information. Research advanced and scalable algorithms in machine learning for use in areas related to advertising technology such as user modeling and profiling and audience ranking and selection. Use machine learning algorithms and techniques, including both supervised and unsupervised, to build predictive models for a variety of applications and use cases related to classification, clustering, recommendation and ranking. Performs parallel computing, and conduct data analysis and develop scalable machine learning algorithm based on big data. Implement machine-learning algorithms and develop software in the above-mentioned areas to support a variety of products offered. Conduct data analysis to gain a deep understanding of raw source data and derived data and construct features for machine learning algorithms to build predictive models. Build out data sets and perform tests on the performance of the predictive models in terms of accuracy, efficiency and scalability. Architect, build and maintain the modeling platform to support various modeling needs.


Requirements: Employer will accept Master’s degree in Mathematics, Engineering, Physics, Computer Science, Machine Learning, or related field; and 2 years of work experience in job offered or 2 years of work experience in a related occupation. Experience must include one year of experience with each of the following:

1)      developing machine learning algorithms and techniques; 

2)      building predictive models;

3)      C++;

4)      Java;

5)      Python;

6)      Scala;

7)      designing, building and using databases;

8)      software development and testing;

9)      parallel computing;

10)  conducting data analysis; 

11)  Spark;

12)  Hive; and

13)  SQL.


Must be available to work on projects at various, unanticipated sites throughout the United States.


CONTACT:  In order to be considered for this position, you must send resume to: [email protected] Please refer to Job #6630.4664.


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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