Manager - Decision Science

Position Summary

Data Scientist with good 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

Necessary Skills

Experience of model development using Python/PySpark libraries. Development on Databricks or Dataiku DSS (Data Science Studio) environment would be a plus

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 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 experience in task management and be able to plan self and teams tasks. Should be able to proactively coarse-correct, basis the current priorities along with their tracking and progress report

Communication Able to convey ideas and information clearly and accurately across forums/team in written or verbal

Education

BE/B.Tech

Work Experience

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)

Behavioural Competencies

Teamwork Leadership

Motivation to Learn and Grow

Ownership

Cultural Fit

Talent Management

Technical Competencies

Problem Solving

Lifescience Knowledge

Communication

Project Management

Attention to PL Impact

Business development

Capability Building / Thought Leadership

Scale of revenues managed / delivered

Scale of Resources Managed