Job Summary: -  

Data Scientist with good hands-on experience of 3+ years in developing state of the art and scalable Machine Learning models and their operationalization, leveraging off-the-shelf workbench production. 

 

Job Responsibilities: -

 

Hands on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.) Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence Good understanding of any of the cloud platform – AWS, Azure or GCP Understanding of Commercial Pharma landscape and Patient Data / Analytics would be a huge plus Should have an attitude of willingness to learn, accepting the challenging environment and confidence in delivering the results within timelines. Should be inclined towards self motivation and self-driven to find solutions for problems. Should be able to mentor and guide mid to large sized teams under him/her

 

Job Requirements: -

Strong experience on Spark with Scala/Python/Java Strong proficiency in building/training/evaluating state of the art machine learning models and its deployment Proficiency in Statistical and Probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, Clustering

Proficiency in Core NLP techniques like Text Classification, Named Entity Recognition (NER), Topic Modeling, Sentiment Analysis, etc. Understanding of Generative AI / Large Language Models / Transformers would be a plus