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Remote mid-level ML role with popular Data Scientist title and broad skillset attracts many qualified applicants.
Requires marketplace and conversational AI expertise, making skills less transferable across unrelated industries.
Explicit years plus mandatory ML, causal inference, RL, production and NLP requirements make filters strict.
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Build and maintain ML and optimisation models for Mrsool's quick-commerce marketplace including supply-demand matching, dynamic pricing, recommendations, and ETA prediction.
Develop AI models for Butler, the conversational ordering system, handling unstructured inputs like text, voice, and images to generate actionable orders.
Design and run A/B and quasi-experiments to derive data-driven decisions and own the full ML model lifecycle including deployment, monitoring, and retraining.
3 to 4 years of professional data science or ML experience in fast-paced startups or large tech enterprises.
Strong skills in A/B testing, causal inference methods (diff-in-diff, instrumental variables, synthetic control) applicable to network/marketplace settings.
Proficient with Python and SQL; experience deploying and maintaining ML pipelines in production environments.
Bachelor's or Master's degree in Computer Science, Statistics, Engineering, or equivalent quantitative discipline.
Experienced with quick-commerce, marketplaces, logistics, ride-hailing or on-demand delivery platforms focusing on two-sided supply and demand dynamics.
Familiarity with NLP or large language models for intent classification, entity extraction, embeddings, relevant to conversational AI features like Butler.
Comfortable using big data and streaming technologies such as Spark and Kafka for real-time model inference and monitoring.