Gen AI Engineer

Academics and Experience requirements

• Bachelor’s or Master’s 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.

If interested, please email me your updated resume at fjayaraj@griddynamics.com along with :

Once I have these, I’ll review and get back to you with the next steps.