Data Scientist (Logistics) at Snoonu – Remote

Data Science
April 24, 2025
Full Time
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Job Description

At Snoonu, we believe that technology has the power to make anything possible.

Our Vision: To be the first Qatari Super App that propels the region and its community through innovation and technology. We envision a global expansion where what we do surpasses norms and limitations every time.

In this position, you will be working and collaborating with ML engineers, backend engineers, researchers, and product engineers in a cross-functional setting. Your core responsibilities will be on research, development, implementation, and testing of algorithms and methods for time series forecasting solutions that optimize our network. Among other things, you are the go-to person on the solution design, performance, and feature design.

Requirements

  • MSc in Data Science, Big Data, AI, Statistics or a related field.
  • 5+ years of experience in data science, machine learning, or statistical modeling.
  • Proficiency in Python, including libraries such as Pandas, NumPy, Scikit-learn, Optuna, and LightGBM, Tensorflow or Pytorch.
  • Deep expertise in machine learning techniques, including supervised and unsupervised learning, advanced feature engineering, and model evaluation.
  • Extensive experience working with time series forecasting, regression, and classification problems, and/or recommendation engines.
  • Practical experience in developing and deploying ML models at scale, including monitoring and retraining pipelines.
  • Practical experience in A/B testing and other experimentation techniques.
  • Strong experience handling large datasets and proficient SQL databases (bigquery, redash, DSQL, or others).
  • Experience with AWS (e.g. ECS, S3, Lambda, Step Functions), GCP (Bigquery, VertexAI or similar), and Databricks for ML model development and deployment.
  • Excellent problem-solving skills and ability to work independently, as well as in a team-oriented, collaborative environment.
  • Strong communication and collaboration skills, with the ability to work effectively within a diverse, cross-functional team.

The following are a plus

  • PhD in CS, ECE, Statistics, or equivalent industrial experience.
  • Proven experience in the delivery and logistics industry, with a strong understanding of its unique operational challenges and optimisation opportunities.

Responsibilities

  • Lead the development and implementation of advanced ML to improve business processes, such as ETAs and preparation times forecasting, demand prediction, and churn analysis.
  • Design and conduct experiments to test and validate models under various scenarios.
  • Fine-tune and deploy Models & applications for real-world use cases.
  • Design and evaluate data-driven experiments, ensuring robustness and real-world applicability.
  • Provide technical leadership in data science, mentoring junior team members, and driving best practices.
  • Translate complex analytical results into actionable business insights, presenting findings to senior leadership and stakeholders.
  • Stay up-to-date with the latest advancements in AI and ML, integrating cutting-edge techniques into business solutions.
  • Collaborate with cross-functional teams, including data scientists, engineers, and business managers, to identify key operational challenges and develop innovative solutions.