Data Scientist

Purpose & Primary Objectives

Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications

Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

Ability to dive deep into problem areas of Machine Learning and look for innovative technology solutions to not only advance the current state of solution, but also to generate new options that can provide significant strategic advantage

Minimum 4 years of experience in developing and deploying Machine Learning, Deep Learning, NLP solutions

Key Responsibilities

Understand business process/ business problems and device Machine Learning solutions to optimize business processes wherever possible.

Formulating machine learning solutions to business metrics, designing features from the data available from many large data sources, training, evaluating, and deploying models in production

Developing high-performance algorithms for precision targeting, testing and implementing these algorithms in scalable, production-ready code; Interacting with other teams to define interfaces and understanding and resolving dependencies

Technical Skills

Bachelors or higher computational science with an emphasis in Machine Learning

Minimum 4 years of experience of writing production quality code.

Experience with traditional as well as modern statistical techniques, including Regression, Support Vector Machines, Regularization, Boosting, Random Forests, and other Ensemble Methods

Experience with end-to-end modelling projects emerging from research efforts

Experience in creating large data feature stores for Machine learning in Teradata or similar databases.