Data Scientist

2 weeks ago

Netanya, Central District, Israel Fetcherr Full time ₪90,000 - ₪120,000 per year

Data Scientist - Deep Learning Based Demand Forecasting

Fetcherr experts in deep learning, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.

We are seeking a talented and self-driven Data Scientist to help advance our machine learning capabilities. The ideal candidate is a motivated, independent thinker with a passion for using machine learning and data to drive business impact.

Responsibilities:

  • Develop and implement state-of-the-art econometric and machine learning models for demand forecasting.
  • Conduct research and experimentation to evaluate novel approaches for improving accuracy, robustness, and scalability.
  • Collaborate with cross-functional teams (including product, data engineering, and backend) to deploy ML systems in production.
Requirements

You'll be a great fit if you have:

  • 3+ years of hands-on experience in data science and machine learning.
  • Proven experience developing and deploying production-grade machine learning models.
  • Degree in Computer Science, Machine Learning, Statistics, or related field.
  • Expertise in time-series forecasting, preferably in demand prediction or related areas.
  • Proficiency in Python and its ML/data stack (e.g., PyTorch or TensorFlow, Pandas, NumPy, Scikit-learn).
  • Solid understanding of ML production workflows (versioning, testing, reproducibility, and deployment).
  • Excellent communication and collaboration skills.
  • Strong data visualization and exploratory data analysis skills.
  • Background in code optimization, containerization (e.g., Docker), CI/CD, or cloud-native architectures.

Nice to have:

  • Master's or PhD in Computer Science, Machine Learning, Statistics, or a related field.
  • Publication(s) in a top-tier, peer-reviewed ML/AI venue (e.g., NeurIPS, ICML, ICLR, AAAI).
  • Experience applying ML in domains like finance, trading, reinforcement learning, or NLP.
  • Familiarity with MLOps tooling and cloud platforms (e.g., GCP, AWS).
  • Experience with workflow orchestration tools like Apache Airflow or Dagster.
  • Participation in competitive programming or data science challenges (e.g., Kaggle).

If you're excited about building impactful AI systems in a high-growth startup environment, and want to help redefine how industries price, forecast, and optimize, we'd love to hear from you.

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