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