Description :

- You would be required to Identify, develop and implement the appropriate statistical techniques, algorithms and Deep learning / ML Models to create new, scalable solutions that address business challenges across industry domains.

- Define, develop, maintain and evolve data models, tools and capabilities.

- Communicate your findings to the appropriate teams through visualizations

- Provide solutions for but not limited to : Object detection/Image recognition, natural language processing, Sentiment Analysis, Topic Modeling, Concept Extraction, Recommender Systems, Text Classification, Clustering , Customer Segmentation & Targeting, Propensity Modeling, Churn Modeling, Lifetime Value Estimation, Forecasting, Modeling Response to Incentives, Marketing Mix Optimization, Price Optimization, GenAI and LLMs.

- Ability to build, train and lead a team of data scientists.

- Follow/maintain an agile methodology for delivering on project milestones.

- Experience applying statistical ideas and methods to data sets to answer business problems.

- Mine and analyze data to drive optimization and improvement of product development, marketing techniques and business strategies.

- Working on ML Model Containerisation.

- Creating ML Model Inference Pipelines.

- Testing and Monitoring ML Models.

Tech Stack :

- Strong Python programming Knowledge - Data Science and Advanced Concepts like Abstract Class, Function Overloading + Overriding, Inheritance, Modular Programming and Reusability

- Working knowledge of Transformers, Hugging face etc..

- Working knowledge in implementing large language modes for enterprise applications.

- Cloud Experience in using Azure services,

- REST API using Flask or fastapi frameworks

- Good to have - Pyspark : Spark Dataframe Operations, SQL functions API, Parallel Execution

- Good to have - Unit testing using Python pytest or Unittest