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Remote, mid-level ML role with generalist title but niche marketplace and RL requirements.
Role requires marketplace, quick-commerce, RL and conversational AI domain expertise, limiting cross-industry transfer.
Explicit 3–4 year requirement plus mandated ML, causal inference, RL, production skills.
Build, deploy, and maintain ML and optimisation models for quick-commerce marketplace functions including supply-demand matching, dynamic pricing, recommendations, and ETA prediction.
Design and execute rigorous A/B and quasi-experiments to inform data-driven decision making across pricing, matching, recommendations, and conversational AI features.
Own end-to-end lifecycle of ML models including feature engineering, monitoring, retraining, and cross-team collaboration to ensure operational stability and continuous improvement.
3 to 4 years of professional data science or ML experience, preferably in fast-paced startups or high-scale tech enterprises.
Strong expertise in experimentation design including A/B tests, power analysis, and causal inference methods relevant to marketplaces/networked settings.
Proficiency in Python and SQL for working with large-scale data and deploying ML pipelines.
Bachelor's or Master's degree in Computer Science, Statistics, Engineering, or equivalent quantitative field.
Experience in quick commerce, marketplaces, logistics, ride-hailing, or on-demand delivery with understanding of two-sided supply-demand dynamics.
Hands-on NLP or LLM experience relevant to conversational AI, including intent classification, entity extraction, or voice data processing.
Comfortable working with big-data streaming tools like Spark and Kafka and implementing real-time ML model inference in production.