Position Summary

Data Scientist with positive hands-on experience of 5+ years in developing state of the art and scalable Machine Learning models and their operationalization, leveraging off-the-shelf workbench production.

Job Responsibilities
Experience of model development using Python/PySpark libraries. Development on Databricks or Dataiku DSS (Data Science Studio) setting would be a plus
Strong experience on Spark with Scala/Python/Java
Robust 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 and experience with LLMs, LSTMs, GRUs, transformers. Familiarity with recommender systems, reinforcement learning.
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.
Logical Thinking – Able to think analytically, use a systematic and logical approach to analyze data, problems, and situations. Be able to notice and call out discrepancies and inconsistencies in information and materials.

Task Management – Should have

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🏢 Axtria
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