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Mrsool

On-demand delivery platform with P2P model

Data Scientist 2

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

  • 3 to 4 years of non-internship professional data science or machine learning experience in fast-paced product startups or high-scale technology enterprises.
  • Solid command of A/B test design, power analysis, and quasi-experimental methods such as difference-in-differences, instrumental variables, and synthetic control, including awareness of interference in marketplace or network settings.
  • Strong grounding in forecasting and at least one of operations research or reinforcement learning applied to allocation, matching, or pricing problems.
  • Proven ability to build, select, and maintain features from large, messy, real-world data.
  • Comfort deploying, monitoring, and maintaining machine learning pipelines, with engineering discipline to keep models reliable in production.
  • Fluency in Python and SQL, and ability to work efficiently against large-scale data.
  • Ability to reason from first principles and deliver high-quality work while balancing reliability, latency, and interpretability trade-offs.
  • Bias toward shipping early and iterating, with a belief in small, incremental changes over large, multi-quarter undertakings.
  • Bachelor's or master's degree in Computer Science, Statistics, Engineering, or an equivalent quantitative field.

Responsibilities

  • Build and maintain machine learning and optimization models across the quick-commerce stack, including supply-demand matching, dynamic and surge pricing, recommendations, ETA prediction, and broader marketplace optimization.
  • Contribute to the AI behind Butler by modeling customer intent from free-form, unstructured text, voice, and images, and mapping it to fulfillable, well-priced orders.
  • Design and run A/B and quasi-experimental studies across pricing, matching, recommendations, and Butler, and turn noisy marketplace data into decisions stakeholders can act on.
  • Engineer high-signal features from order events, courier traces, geospatial signals, pricing configurations, and conversational text and voice data.
  • Own models throughout their lifecycle, including data pipelines, training, deployment, monitoring, and retraining, and respond when a model or configuration drifts.
  • Collaborate with product managers, engineers, DevOps, operations, and other squads to deliver data-driven experiences and diagnose live issues such as mispriced brackets or elevated city failure rates.
  • Monitor model and metric health, instrument work with logging and observability, and contribute to reliable, repeatable analysis and deployment practices.
  • Identify opportunities to improve measurement, modeling, and processes through small, incremental changes.

Desired Qualifications

  • Hands-on experience in quick commerce, marketplaces, logistics, ride-hailing, or on-demand delivery, with understanding of two-sided supply and demand dynamics.
  • NLP or LLM experience, including intent classification, entity extraction, embeddings, or conversational and voice data relevant to Butler.
  • Comfort with streaming and big-data tools such as Spark and Kafka, and real-time inference.

About the Company

Mrsool

On-demand delivery platform with P2P model

Mrsool operates an on-demand delivery marketplace in Saudi Arabia that connects customers with couriers. Users describe the service they need in a chat, and available couriers bid their price to fulfill the request, after which the user picks a courier to complete the job. This bid-based, chat-driven model creates a scalable, person-to-person marketplace that spreads across cities and users. The goal is to grow a large, self-regulating network that efficiently matches buyers with couriers through simple chat interactions.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Riyadh, Saudi Arabia
Founded
2015

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