Associate Divisional Manager - Data Sciences

Job Purpose This role includes designing and building AI/ML products at scale to improve customer Understanding & Sentiment analysis, recommend customer requirements, recommend optimal inputs, Improve efficiency of Process. This role will collaborate with product owners and business owners.

Key Responsibilities Leading a team of junior and experienced data scientists Lead and participate in end-to-end ML projects deployments that require feasibility analysis, design, development, validation, and application of state-of-the art data science solutions. Push the state of the art in terms of the application of data mining, visualization, predictive modelling, statistics, trend analysis, and other data analysis techniques to solve complex business problems including lead classification, recommender systems, product life-cycle modelling, Design Optimization problems, Product cost & weigh optimization problems. Leverage and enhance applications utilizing NLP, LLM, OCR, image based models and Deep Learning Neural networks for use cases including text mining, speech and object recognition Identify future development needs, advance new emerging ML and AI technology, and set the strategy for the data science team Cultivate a product-centric, results-driven data science organization Write production ready code and deploy real time ML models; expose ML outputs through APIs Partner with data/ML engineers and vendor partners for input data pipes development and ML models automation Provide leadership to establish world-class ML lifecycle management processes

Qualifications Job Requirements MTech / BE / BTech / MSc in CS or Stats or Maths

Experience Over 10 years of Applied Machine learning experience in the fields of Machine Learning, Statistical Modelling, Predictive Modelling, Text Mining, Natural Language Processing (NLP), LLM, OCR, Image based models, Deep learning and Optimization Expert Python Programmer: SQL, C#, extremely proficient with the SciPy stack (e.g. numpy, pandas, sci-kit learn, matplotlib) Proficiency in work with open source deep learning platforms like TensorFlow, Keras, Pytorch Knowledge of the Big Data Ecosystem: (Apache Spark, Hadoop, Hive, EMR, MapReduce) Proficient in Cloud Technologies and Service (Azure Databricks, ADF, Databricks MLflow)

Functional Competencies A demonstrated ability to mentor junior data scientists and proven experience in collaborative work environments with external customers Proficient in communicating technical findings to non-technical stakeholders Holding routine peer code review of ML work done by the team Experience in leading and / or collaborating with small to midsized teams Experienced in building scalable / highly available distribute systems in production Experienced in ML lifecycle mgmt. and ML Ops tools & frameworks