As a Data Scientist in our Decision Sciences R&D organization, you will be responsible for researching and building machine learning, natural language processing, and recommender system applications to extend Conversant’s personalization platform. Conversant’s business is based on analyzing anonymized data at internet scale and evaluating more than 1 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 researching and developing models, algorithms, and applications; analyzing raw source data and derived data; presenting findings; and building tools and analyses for new and existing products.
- Develop an understanding of Conversant’s personalization platform and proprietary datasets.
- Use your machine learning expertise to research and recommend the best approaches to solving our technology and business problems.
- Design, implement, and validate your solutions in Apache Spark, Apache Hive, using Scala or Python on a large state-of-the-art cluster.
- Work with our Engineering teams to integrate your solutions into Conversant’s platform.
- Participate fully in our collaborative approach to research and applications projects.
- A Ph.D., (or Master’s degree plus at least 3 years’ relevant experience), in Computer Science, Statistics, Linguistics, Electrical Engineering, Mathematics, Economics, Physics, or a related scientific discipline.
- Research experience and coursework in Machine Learning.
- Fluency in programming.
- Experience with large data sets.
- Strong understanding of statistics and modeling techniques.
- Desire to work in a highly collaborative environments.
ADDITIONAL USEFUL BUT NOT REQUIRED SKILLS
- Experience with distributed computing, such as Hadoop, Spark, or related technologies.
- Familiarity with SQL, Scala, Python, or Java.
- Experience with Recommender Systems, Natural Language Processing, or Information Retrieval.
- Experience with mathematical optimization, control theory, time-series analysis.