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.

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.

Qualification :

- B-Tech or BE in Computer Science / Computer Applications from Tier 1-2 college with 3+ years of proven experience in the field of Advanced Analytics or Machine Learning.

- Masters degree in Machine Learning / Statistics / Econometrics, or related discipline from Tier 1-2 college with 3+ years of experience.

Must have Skills :

- Real-world experience in implementing machine learning/statistical/econometric models/advanced algorithms.

- Breadth of machine learning domain knowledge.

- Experience in application of machine learning algorithms (classification, regression, deep learning, NLP, etc.

- Experience with a ML/data-centric programming language (such as Python, Scala, or R) and ML libraries (pandas, numpy, scikit-learn, etc.

- Experience with Apache Hadoop / Spark (or equivalent cloud-computing/map-reduce framework).

Skills that give you an edge :

- Strong analytical skills to solve and model complex business requirements are a plus.

- With life sciences or pharma background.