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Hybrid Bangalore mid-level ML role with common Data Scientist title and broad skillset increases competition.
ML and NLP skills are transferable, but consumer-goods domain knowledge raises sensitivity to medium.
Mandatory 2+ years plus specific ML, NLP, image-processing, and tooling requirements make filtering strict.
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Develop and improve ML models for NLP, Image Processing, and supervised/unsupervised learning tasks based on client feedback.
Formulate hypotheses and translate industry-specific knowledge into applicable models.
Ensure data quality and effectively communicate insights through written and visual formats.
2+ years of relevant work experience in Mathematics, Physics, Natural Sciences, or Engineering fields related to data science.
Advanced Python programming skills including git merge-request workflows, scripting, and basic web app development.
Experience with ML model maintenance: performance measurement, labeling, retraining, and documentation.
Proficiency in classical ML techniques, NLP, deep learning understanding, and data visualization frameworks.
Demonstrates strong coding discipline with documentation, linting, styling, reproducibility, and test-driven development.
Capable of managing ML model lifecycle including experiment tracking and integration with existing models.
Experienced in communicating technical status, solutions, and insights clearly to business stakeholders.