Academics and Experience requirements :

- Bachelors or Masters in Computer Science / Statistics / Mathematics /Data Science/ MBA.

- 4+ years of experience as data science (ideally as a team lead), leading scalable developments of data scientist and ML engineers, preferably focused on development of reusable analytical toolkits, ideally in the field of time series forecasting.

- 4+ years of experience building solutions in the supply chain space.

- Demand planning would be a plus.

- 6+ years working in a team to deliver production level analytic solutions.

- Fluent in git (version control).

- 6+ years experience in ETL and/or data wrangling techniques.

- 6+ years of experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems (Random Forest/Decision Trees, XGBoost, LightGBM, etc.), and in particular time series forecasting (Time series, ARIMA, ARIMAX, Holts Winter, Regression analysis, etc.), hypothesis testing.

- Experiences with Deep Learning are a plus.

- 4+ years of experience in model explainability.

- 6+ years of experience in developing business-centered statistical/ML modeling with the use of industry tools, preferably Python or Scala based.

- Ability to design and support technical architecture.

- Experience with distributed machine learning.

- Business storytelling and communicating data insights in business consumable format.

- Vast experience with at least one Visualization tool.

- Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities.

- Experience with Agile methodology to organize team work and analytics.