Assistant Manager - Data Science

Experience: 6 to 8 years

Location: Chennai, Tamil Nadu

We are looking for a Assistant Manager - Data Science for one of our clients, a leading DATA analytics company who present for nearly two Decades and have featured in Deloitte’s Fast 50 (Asia Pacific), Recognized by Frost & Sullivanas as “Analytics solution provide of the year”, “AI game changer” by NASSCOM and several other recognitions

Responsibilities:

The following are must-haves:

• A strong level of proficiency in python programming and ML phases life cyle.

• Practical knowledge and working experience on Statistics and Operation Research methods.

• Practical knowledge and working experience in tools and frameworks like Flask,PySpark,Pytorch, streamlit.

• Practical knowledge in Analytics/AI-ML AWS services like Sagemaker, Canvas, Bedrock.

• Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc.

• Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively

• handle readily available stanford, IBM, Azure, Open AI NLP models.

• Good understanding of SQL from a perspective of how to write efficient queries for pulling the data from database.

• Hands on experience on any version control tool (github, bitbucket).

• Hands on experience in Model training and deployment.

The candidate will be required to:

• Comprehend business issues and propose valuable business solutions.

• Design Factual or AI/profound learning models to address business issues.

• Design Statistical Models/ML/DL models and deploy them for production.

• Formulate what information is accessible from where and how to augment it.

• Develop innovative graphs for data comprehension using d3js, dashplotly.

Skills:

• 6 to 8 years in the Data Science domain

• Flask,PySpark,Pytorch, streamlit.Practical knowledge in Analytics/AI-ML AWS services like Sagemaker, Canvas, Bedrock.

• Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc.

• Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively handle readily available stanford, IBM, Azure, Open AI NLP models