We are looking for a data science researcher to work and develop engagement and recommendation models that explain and generate insights about user behaviors from audience viewership data. The ideal candidate will feel very comfortable with ML and DL (supervised and unsupervised), and have strong knowledge in linear algebra and probability theory. The candidate should also feel comfortable with Python and the relevant ML libraries, as well as with SQL and big data technology and terminology.
- Solid understanding of applied math and statistics
- Experience with algorithm development.
- Experience with SW feature development and deployment in big data env.
- Experience with SQL databases and big data environment and tools
- The person holding this skill set should be able to read an academic paper and implement the algorithm in the paper.
- Experience with research and development of ML and DL processes, mostly in the areas of recommendation, NLP, time series analysis, and anomaly detection.
- Familiarity with dominant libraries and frameworks.