Conversant analyzes anonymized, privacy-safe data at internet scale: we handle 200B+ of online interactions a day and have $3.8 trillion in multichannel purchases in our database. The Decision Sciences group is a collaborative Research & Development team that continually enhances Conversant’s award-winning personalization platform through a combination of data science, machine learning, AI, natural language processing, recommender systems, computer science, and more.
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. 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 data; presenting findings; and building tools and analyses for new and existing products.
RESPONSIBILITIES
- 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.
REQUIREMENTS
- 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 environment.
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, or causal inference.