Senior Time-Series ML Scientist — Logistics Optimisation

Snoonu; Qatar; Remote; QAR 120,000 - 200,000; Full time

Benefits offered by this job

Global Vibes

Brain Boosters

Flexible Time Off

Agile Everything

Great Place to Work

Job summary

Snoonu in Qatar is seeking a data science leader to drive time series forecasting and optimisation for logistics. You will design and deploy predictive models, orchestrate optimization solvers, and work with cross-functional teams to translate insights into business actions.

Responsibilities include rigorous experimentation, model monitoring, and mentoring junior colleagues while staying ahead of AI/ML advances in logistics.

Qualifications

• MSc in Data Science, Statistics, Applied Mathematics, Computer Science, or related field.
• 5+ years in data science, ML, or statistical modelling with focus on time series forecasting and/or optimisation.
• Experience with time series methods (ARIMA, Prophet, LightGBM, TFT, DeepAR, N-BEATS).
• Proficiency in Python with Pandas, NumPy, Scikit-learn.
• Experience deploying ML models at scale with monitoring and retraining pipelines.

Responsibilities

• Lead research, development, and implementation of time series forecasting models for logistics optimisation.
• Design optimization algorithms and solvers to improve route planning and resource allocation.
• Run experiments to validate models under real-world scenarios for robustness.
• Fine-tune, deploy, and monitor ML models in production; maintain retraining pipelines.
• Collaborate cross-functionally with ML engineers, backend engineers, researchers, and product teams.
• Conduct A/B tests to measure impact on logistics KPIs and drive improvements.
• Translate analytical results into actionable business insights for senior leadership.
• Provide technical leadership and mentorship in modelling, experimentation, and code quality.
• Stay updated with advances in AI/ML and operations research for logistics solutions.

Skills

Time series forecasting

Optimization

Experimentation

Python

SQL

Cloud platforms

ML deployment

A/B testing

Leadership

Communication

Education

MSc in Data Science

PhD preferred

Tools

OR-Tools

PuLP

LightGBM

TensorFlow

PyTorch

BigQuery

Redash

Pandas

NumPy

Scikit-learn

Job description

Snoonu in Qatar is seeking a data science leader to drive time series forecasting and optimisation for logistics. You will design and deploy predictive models, orchestrate optimization solvers, and work with cross-functional teams to translate insights into business actions.

Responsibilities include rigorous experimentation, model monitoring, and mentoring junior colleagues while staying ahead of AI/ML advances in logistics.