Job
Description
Job Type: Full time Job description: Experience of at least 3 years in developing models using Python/PySpark libraries. Experience with Databricks or Dataiku DSS (Data Science Studio) would be an added advantage. Strong experience with Scala/Python/Java and Spark is required. Strong proficiency in developing, training, and evaluating state-of-the-art machine learning models and deploying them is required. Proficiency in statistical and probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, and Clustering is needed. Proficiency in core NLP techniques such as Text Classification, Named Entity Recognition (NER), Topic Modeling, and Sentiment Analysis is required. Understanding Generative AI, Large Language Models, and Transformers would be an added advantage. Have hands-on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, and Matplotlib. Proficiency in Python and common Machine Learning frameworks such as TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML, and OpenAI is required. Experience of working in large teams and using collaboration tools like GIT, Jira, and Confluence is a must. Good understanding of any of the cloud platforms such as AWS, Azure, or GCP is required. 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.
