Data Scientist- Deep Learning & Model Building

Job Description

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: - 1. Hands on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib 2. Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.) 3. Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence 4. Good understanding of any of the cloud platform AWS, Azure or GCP 5. Understanding of Commercial Pharma landscape and Patient Data / Analytics would be a huge plus 6. 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. 7. Should be able to mentor and guide mid to large sized teams under him/her Job Requirements: - 1. Strong experience on Spark with Scala/Python/Java 2. Strong proficiency in building/training/evaluating state of the art machine learning models and its deployment 3. Proficiency in Statistical and Probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, Clustering 4. 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 OR - Master's 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. We will provide (Employee Value Proposition) Offer an inclusive environment that encourages diverse perspectives and ideas Deliver challenging and unique opportunities to contribute to the success of a transforming organization Opportunity to work on technical challenges that may impact across geographies Vast opportunities for self-development: online Axtria Institute, knowledge sharing opportunities globally, learning opportunities through external certifications Sponsored Tech Talks & Hackathons Possibility to relocate to any Axtria office for short and long-term project