Company:
Epsilon
Location: Chicago
Closing Date: 17/11/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
Job Description
How You’ll Make an Impact
As a Data Scientist in our Decision Sciences R&D organization, you will be responsible for researching and building optimization, control theory, simulation, and machine learning applications to extend Epsilon Digital’s ad personalization platform. Epsilon’s business is based on analyzing anonymized data at Internet scale and evaluating more than one trillion advertising opportunities per month in real-time. You will work on real-world problems as part of our highly collaborative R&D team, and your 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; and presenting findings.
Key Responsibilities:
Understand and Innovate: Gain deep insights into Epsilon’s ad personalization platform and proprietary datasets to drive innovation.
Research and Development: Apply your expertise in optimization, control theory, simulation, or machine learning to develop and recommend solutions for complex technology and business challenges.
Solution Implementation: Design, implement, and validate advanced solutions using Apache Hive, Spark, Python, or Scala on large-scale computing clusters.
Collaborative Integration: Work closely with Engineering teams to integrate your solutions seamlessly into Epsilon’s platform.
Active Participation: Engage fully in our collaborative research and application projects, contributing to the team’s collective success.
Skills & Experience:
Educational Background: Ph.D. in Computer Science, Operations Research, Electrical Engineering, Statistics, Mathematics, Physics, Economics, or a related scientific discipline.
Technical Expertise: Demonstrated research experience and coursework in optimization, control theory, machine learning, or simulation.
Programming Proficiency: Strong fluency in programming and experience with large data sets.
Analytical Skills: In-depth understanding of modeling and statistical techniques.
Team Collaboration: Enthusiasm for working in a collaborative, dynamic environment.
Additional Skills (Preferred but Not Required):
Distributed Computing: Experience with Hadoop, Spark, or similar technologies.
Technical Tools: Familiarity with Python, SQL, or Scala.
Domain Knowledge: Experience in modeling or analyzing consumer behavior, market dynamics, or auctions.
How You’ll Make an Impact
As a Data Scientist in our Decision Sciences R&D organization, you will be responsible for researching and building optimization, control theory, simulation, and machine learning applications to extend Epsilon Digital’s ad personalization platform. Epsilon’s business is based on analyzing anonymized data at Internet scale and evaluating more than one trillion advertising opportunities per month in real-time. You will work on real-world problems as part of our highly collaborative R&D team, and your 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; and presenting findings.
Key Responsibilities:
Understand and Innovate: Gain deep insights into Epsilon’s ad personalization platform and proprietary datasets to drive innovation.
Research and Development: Apply your expertise in optimization, control theory, simulation, or machine learning to develop and recommend solutions for complex technology and business challenges.
Solution Implementation: Design, implement, and validate advanced solutions using Apache Hive, Spark, Python, or Scala on large-scale computing clusters.
Collaborative Integration: Work closely with Engineering teams to integrate your solutions seamlessly into Epsilon’s platform.
Active Participation: Engage fully in our collaborative research and application projects, contributing to the team’s collective success.
Skills & Experience:
Educational Background: Ph.D. in Computer Science, Operations Research, Electrical Engineering, Statistics, Mathematics, Physics, Economics, or a related scientific discipline.
Technical Expertise: Demonstrated research experience and coursework in optimization, control theory, machine learning, or simulation.
Programming Proficiency: Strong fluency in programming and experience with large data sets.
Analytical Skills: In-depth understanding of modeling and statistical techniques.
Team Collaboration: Enthusiasm for working in a collaborative, dynamic environment.
Additional Skills (Preferred but Not Required):
Distributed Computing: Experience with Hadoop, Spark, or similar technologies.
Technical Tools: Familiarity with Python, SQL, or Scala.
Domain Knowledge: Experience in modeling or analyzing consumer behavior, market dynamics, or auctions.
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