Data Scientist II

This is a fully remote position, open to applicants in India.

📋 Description

• What You Will Do💡

• - Marketplace Modelling: Develop and sustain machine learning and optimization models throughout the quick-commerce ecosystem — including supply-demand matching, dynamic and surge pricing, recommendations, ETA prediction, and overall marketplace optimization.

• - Butler & Conversational AI: Play a key role in enhancing the AI behind Butler, Mrsool's unique conversational ordering platform — interpreting customer intent from unstructured requests (text, voice, images) and translating it into fulfillable, competitively priced orders.

• - Experimentation & Causal Inference: Create and implement experiments (A/B and quasi-experimental) across pricing, matching, recommendations, and Butler, converting noisy marketplace data into actionable insights for stakeholders.

• - Feature Engineering & Data Craft: Extract high-value features from complex, real-world data — including order events, courier traces, geospatial signals, pricing configurations, and conversational text/voice — as a fundamental and ongoing aspect of the role.

• - Production ML: Take ownership of your models throughout their lifecycle — encompassing data pipelines, training, deployment, monitoring, and retraining — and address any model or configuration drifts.

• - Cross-Functional Collaboration: Work effectively with product managers, engineers, DevOps, operations, and other teams to provide seamless, data-driven experiences and assist in diagnosing live issues (e.g., mispriced brackets, increased failure rates in specific locations).

• - Operational Excellence: Actively monitor model and metric health, ensure your work is properly logged and observable, and contribute to reliable and repeatable analysis and deployment practices.

• - Continuous Improvement: Seek out opportunities to refine measurement, modeling, and processes; prefer small, incremental changes that accumulate over time.

⛳️ Requirements

• What Are We Looking For❓

• - Years of Experience: 3 to 4 years of relevant professional experience in data science or machine learning, preferably in fast-paced product startups or large-scale tech companies.

• - Experimentation & Causal Inference: A strong understanding of A/B test design, power analysis, and quasi-experimental methods (such as diff-in-diff, instrumental variables, synthetic control), including an awareness of interference in marketplace/network environments.

• - ML & Optimisation Depth: A robust foundation in forecasting and at least one area of operations research or reinforcement learning related to allocation, matching, or pricing challenges.

• - Feature Engineering: Demonstrated ability to construct, select, and maintain features from extensive, messy real-world data.

• - Production Engineering: Proficient in deploying, monitoring, and sustaining machine learning pipelines, with the technical discipline to ensure model reliability in production settings.

• - Technical Toolkit: Proficient in Python and SQL, with the capacity to work effectively with large-scale data.

• - Problem-Solving Mindset: An aptitude for thinking from first principles and a proven history of delivering high-quality work while managing trade-offs such as reliability, latency, and interpretability.

• - Iterative Mindset: An inclination towards early shipping and iteration; a belief in making small, incremental changes rather than undertaking large, multi-quarter projects.

• - Education: Bachelor's or Master's degree in Computer Science, Statistics, Engineering, or another equivalent quantitative discipline.

• Who Will Excel❓

• - Data scientists with practical experience in quick commerce, marketplaces, logistics, ride-hailing, or on-demand delivery, who grasp two-sided supply/demand dynamics.

• - Individuals with NLP/LLM experience — including intent classification, entity extraction, embeddings, or conversational/voice data — directly applicable to Butler.

• - Engineers familiar with streaming/big-data tools (like Spark, Kafka) and real-time inference.

• - High-agency individuals who approach their models as products and effectively collaborate across differing perspectives.

🏝️ Benefits

• **What We Offer You❗**

• - Inclusive and Diverse Environment: We promote an inclusive and diverse workplace that values innovation and provides remote work options.

• - Competitive Compensation: Our compensation packages are highly competitive and may include potential share options for specific roles.

• - Personal Growth and Development: We are dedicated to your personal and professional growth, offering regular training and an annual learning stipend to support your career advancement in a dynamic setting.

• - Autonomy and Mentorship: You will have a significant degree of autonomy in your role, with the backing of mentorship and ambitious objectives that facilitate both your success and the company's growth.