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
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