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Tier-1 brand plus a mid-level, generalist ML role in metros creates high candidate competition.
Core ML/NLP skills transfer across industries, though logistics-specific simulation knowledge increases domain specificity.
Explicit three-year level, master's preference, and required ML/NLP skills make screening strict.
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Analyze strategic business objectives and drive data-driven decision making using advanced analytical research.
Develop, implement, and optimize machine learning algorithms, predictive analytics models, and natural language processing techniques for extracting insights from large datasets.
Manage data science projects end-to-end, including prototyping applications, automating solutions, designing network simulation models, and communicating complex findings effectively.
Master’s degree or equivalent in Computer Science, MIS, Mathematics, Statistics, or similar discipline.
Work Experience Required: Between 2 to 5 years depending on seniority level (Standard I: 2 years, Standard II: 3 years, Senior I: 4 years, Senior II: 5 years).
Proficiency in statistical and mathematical programming, data modeling, machine learning, predictive analytics, and natural language processing.
Fluency in English.
Experienced in handling complex data science projects including machine learning model development and network simulation design.
Skilled in communicating technical and analytical information effectively through visualization and storytelling.
Able to prototype applications and develop automated solutions to improve operational efficiency within a business context.