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Mid-level generalist Sr Data Scientist at a well-known conglomerate increases candidate competition.
Core ML, MLOps, and Python skills are broadly transferable across industries.
Explicit 4–6 years plus mandatory Python, ML, and MLOps skills increases shortlisting strictness.
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Lead end-to-end machine learning workflows including problem identification, data exploration, feature engineering, model development, evaluation, and documentation.
Develop and optimize predictive models such as tree-based algorithms, linear models, time-series, and LLMs applying experimental and statistical evaluation methods.
Collaborate with cross-functional teams to deploy, monitor, and update production AI models, driving improvements in KPIs like conversion rates and cost-efficiency.
4 to 6 years of hands-on experience applying machine learning to real-world problems.
Proficiency in Python (pandas, NumPy, scikit-learn) and deep learning frameworks (PyTorch or TensorFlow).
Bachelor's degree in Engineering (B.Tech/BE) or related technical field, preferably Computer Science, Electrical Engineering, or IT.
Experience with MLOps, productionizing models, and model lifecycle management including drift detection and continuous improvement.
Experienced in translating complex business problems into scalable machine learning solutions with rigorous analysis.
Proven ability to work effectively in cross-functional teams, communicating technical concepts to non-technical stakeholders.
Detail-oriented with strong commitment to model quality, documentation, ethical AI practices, and continuous learning.