AM-Data Science
1 month ago
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 Deloittes 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
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