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Senior Data Scientist - AI Team

Snapp · Tehran

New
Onsite Senior 🇬🇧 English
Python NumPy Pandas Scikit-learn SQL PyTorch TensorFlow Causal inference Uplift modeling

Job description

About the role

Snapp is hiring a Senior Data Scientist for its AI team in Tehran. The role leads the formulation, modeling and evaluation of complex real-world decision problems using statistics, machine learning and optimization, and provides data-driven guidance for strategic decisions in the ride-hailing and urban mobility marketplace.

Key responsibilities

  • Design, develop and validate statistical and machine-learning models supporting large-scale decision-making and marketplace policy design.
  • Translate business challenges into analytical problems using probabilistic modeling, optimization and causal inference.
  • Apply AI approaches such as reinforcement learning and LLM-based decision models (Jev, Clef), with calibration, thresholds and evaluation frameworks.
  • Design and analyze A/B tests, quasi-experiments, uplift and response models to measure the impact of decisions and policies.
  • Build interpretable models that explain mechanisms and quantify trade-offs, and work with data and ML engineers to deploy production-ready models.
  • Define and monitor metrics for system performance, user experience and marketplace health, and mentor junior data scientists.

Required profile

  • 5+ years as a Data Scientist, or 3+ years with demonstrated end-to-end ownership of high-impact modeling decisions.
  • Strong theoretical knowledge of probability, statistics, machine learning, optimization and causal inference (e.g. difference-in-differences, synthetic control, uplift modeling).
  • Strong analytical and critical thinking, and excellent communication with non-technical stakeholders.

Required skills

  • Python for data science (NumPy, Pandas, Scikit-learn); PyTorch or TensorFlow is a plus.
  • Strong SQL and experience with large-scale analytical datasets.
  • Hands-on experimentation, metric definition, experiment design and statistical power analysis.
  • Nice to have: decision models returning calibrated probabilities, reinforcement learning or contextual bandits, and practical use of LLMs and AI coding assistants.

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Published 19 hours ago

Expires 1 month from now

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Snapp

Tehran