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
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