Senior Data Scientist — Time Series & Logistics Optimizer

Snoonu; Doha; On-site; QAR 350,000 - 600,000; Full time

Benefits offered by this job

Global Vibes – work with a worldwide $

Brain Boosters – learning budgets

Builder’s Playground – autonomy

Flexible Time Off

Agile Everything

Job summary

Snoonu in Qatar is seeking a senior data scientist to lead the research, development, and deployment of time series forecasting and optimization models for logistics, including ETA prediction and route planning.

You will collaborate with ML engineers, backend teams, and product managers, run rigorous experiments, deploy scalable pipelines, and mentor juniors to raise modelling standards.

Join a fast‑growing team with global exposure, learning budgets, autonomy, and flexible time off.

Qualifications

• MSc in data science or related field; PhD is a plus.
• At least 5 years in data science or ML with time series focus.
• Strong Python experience and model deployment exposure.

Responsibilities

• Lead research, development, and deployment of forecasting and optimization models for logistics.
• Design optimization solvers for route planning and resource allocation.
• Run rigorous experiments to validate models under real-world scenarios.
• Deploy, monitor, and retrain ML models and pipelines at scale.
• Collaborate with ML, backend, researchers, and product teams.
• Lead experiments (A/B tests) and translate results to business insights.

Skills

Time series forecasting

Python

Model evaluation

Experimentation

SQL

Communication

Education

MSc in data science / related field

PhD (nice to have)

Tools

OR-Tools

PuLP

TensorFlow / PyTorch

Scikit-learn

LightGBM

BigQuery

Job description

Snoonu in Qatar is seeking a senior data scientist to lead the research, development, and deployment of time series forecasting and optimization models for logistics, including ETA prediction and route planning.

You will collaborate with ML engineers, backend teams, and product managers, run rigorous experiments, deploy scalable pipelines, and mentor juniors to raise modelling standards.

Join a fast‑growing team with global exposure, learning budgets, autonomy, and flexible time off.