Sportism - Senior Data Scientist/Engineer

Job overview:

Are you obsessed with solving complex consumer choice problems? Do you like getting your hands dirty with advanced mathematical and statistical concepts in the form of machine learning algorithms? Then we are looking for you!

We have a unique creative and consumer-centric approach to provide foundational algorithms that provide forward-looking business solutions to our clients - global/regional leaders in banking, airline, retail verticals. Through technical implementation, optimization, and turnkey solutions, the data science team builds world-class choice algorithms that form the core of our platform as well as drive the decisions of our clients.

We're looking for a high performer and team player who will excel in a fun filled, fast-moving startup environment and help us achieve our mission - to simplify the world's choices.

Experience:

- 5+ years of experience with developing solutions using machine learning, operation research and pattern searching methods on large scale data.

- Good understanding on statistical models like hierarchical models, stochastic models, time series, survival and econometric models

- Expert in at least one of the deep learning frameworks such as PyTorch, MxNet, Tensorflow.

- Hands-on experience in using Spark (Scala or Pyspark) to process data at large scale and database schema design for ML pipelines a must

- Contribution to open-source ML packages/research publications will be a huge bonus

Education:

B.E/B.Tech/MS in Machine Learning, Computer Science, Applied Statistics, Mathematics or related field. PhD is a plus

Responsibilities:

- Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods backed with metrics as needed.

- Collaborate with technical and non-technical business partners to develop analytics and metrics for the business requirements

- Take charge of end to end delivery of machine learning models including regularly testing and maintain analytical models to improve efficiency and keep up with changing business needs

- Be able to define and drive test methodologies/validations on the solutions provided

- Research and develop analysis, forecasting, and optimization methods to improve the quality of customer facing products