Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
OR equivalent experience.
3+ years of industry work experience in Python, SQL, R, machine/deep learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment.
Preferred Qualifications :
Experience with programming, e.g. Java, C#.
Experience on large scale computing systems like COSMOS, Hadoop, MapReduce and/or similar systems.
Familiarity with deep learning toolkits like - PyTorch, TensorFlow, etc.
Self-driven and ability to deliver ambiguous projects with incomplete or dirty data.
Responsibilities
Ability to conceptualize, design and build an efficient data pipeline that can train, test and deploy high quality models into production to run at scale.
Partner with teams to identify and explore opportunities for the application of machine learning and predictive analysis.
Communicate with technical and non-technical audiences and contribute modelling expertise as a team player.