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Strong brand, popular data scientist role, and metro location increases candidate competition.
Core ML and production engineering skills are transferable across industries, though domain experience is valuable.
Role requires specific ML/AI production skills and frameworks, making technical filters stringent.
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Lead end-to-end data science projects including data analysis, feature engineering, model selection, implementation, debugging, and maintenance in production environments.
Develop and deploy machine learning and deep learning models, including computer vision and tabular data solutions.
Handle data wrangling and manipulation using Python libraries such as Pandas and Dask, and utilize frameworks like PyTorch, TensorFlow, or Keras for model development.
Bachelor’s or advanced degree in computer science, engineering, applied mathematics, economics, physics, statistics, or related data-intensive field.
Professional experience as ML Engineer or Data Scientist involving machine learning, deep learning, data modeling, optimization algorithms, and network analysis in production settings.
Experience with at least one of the following: PyTorch, TensorFlow, or Keras.
Strong skills in Python data science libraries such as Pandas and Dask.
Experience working on multiple machine learning projects in production settings, demonstrating end-to-end system design expertise.
Familiarity with deployment and maintenance of models in production environments with strong problem-solving and algorithmic solution skills.
Relevant experience in the development sector or Indian governance, and knowledge of GIS tools or SQL considered strong pluses but not mandatory.