Ph.D, Data Scientist (remote) at Epsilon #vacancy #remote

Job Description

In this role, you will contribute to research initiatives and develop enhancements to Epsilon’s CORE Personalization Platform to continually increase the capabilities of Epsilon’s digital marketing businesses.

We prioritize analytical thinking, creativity and computer science skills over ad tech industry experience.

If using internet-scale data to drive business impact excites you, and you enjoy the kind of research that starts with a blank sheet of paper that turns ideas into a new technological reality, we want to talk to you.

Responsibilities

Individually contribute to data science and machine learning R&D projects

Use your data science, machine learning, and/or computer science skills to conduct research and contribute to solutions to technology and business problems

Contribute to projects from early-stage research through development

Implement and optimize state-of-the-art algorithms in distributed environments

Develop an understanding of Epsilon PeopleCloud Digital Media Solutions personalization platform and proprietary datasets

Participate fully in our collaborative approach to research and applications projects

Qualifications

Ph.D. in a computational, mathematical, engineering, or scientific field

Fluency in computer programming, data structures, and algorithm design

Proven analytic and modeling skills

Proven ability to conduct research projects

Research experience in a computational area such as data science, computer science, machine learning, artificial intelligence, statistics, or graph algorithms

Verbal and written communication skills, including the ability to summarize technically complex information for a non-technical audience

Organizational, motivational, and interpersonal skills

Additional, But Not Required Skills

Spark libraries

Scala programming

Python programming

SQL queries

Experience with distributed computing

Experience with Hadoop and cloud databases

Demonstrated proficiency working with business and technical teams to integrate algorithms into product platforms on large data sets

R&D Scala SQL Data Science Python Apache Spark Machine Learning Computer Science Hadoop algorithms

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