Data Scientist Engineer

Posted 24 Days Ago
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Tel Aviv, ISR
In-Office
Mid level
Artificial Intelligence • Software
The Role
Design and implement pricing decision logic and optimization models in production-quality Python. Translate business rules into mathematical constraints, validate model behavior with data, collaborate with Solution Architects and Data Engineers to integrate models into Dagster pipelines.
Summary Generated by Built In
Description

Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model - a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data - not personal data - with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul.

We are looking for a Data Science Engineer to design and implement the decision-making logic of our Price Optimizer. You will focus on translating complex business rules into mathematical models and production-ready Python code.

Your primary mission is to build the "brain" of our system. You will work at the intersection of Data Science and Product, ensuring our simulation and optimization engines accurately reflect real-world pricing strategies and market dynamics. While you will write production code, you will rely on our Data Engineers for ETL pipelines orchestration and distributed compute scaling.

Responsibilities:

  • Implement Business Logic: Translate intricate pricing rules and commercial strategies into robust Python code and mathematical constraints.
  • Refine Optimization Models: Develop and tune the simulation and revenue management algorithms that drive our pricing recommendations.
  • Write Clean Code: Contribute high-quality, tested, and maintainable code to the core logic repositories.
  • Analyze & Improve: Use data to validate model behavior and identify edge cases where business rules clash with algorithmic outputs.
  • Collaborate: Partner with Solution Architects to define logic requirements and with Data Engineers to integrate your models into the Dagster pipelines.
Requirements

You'll be a great fit if you have...

  • 3+ years of experience in Data Science or Algorithmic Development with Python.
  • Proven ability to translate complex business requirements into code and logical rules.
  • Strong background in Mathematical Optimization, Simulation, or Logic Programming.
  • Fluency in the PyData stack (Pandas, NumPy, SciPy) and SQL
  • Experience writing production-quality code (not just notebooks) - you understand modular design and unit testing.
  • Familiarity with orchestration frameworks like Dagster or Airflow (from a user/logic perspective).
  • BSc/MSc in Mathematics/ physics/ statistics/ Computer Science.

Nice to Have:

  • Experience in Revenue Management, Air Travel, or Logistics domains.
  • Understanding of Derivative-Free Optimization.
  • Clickhouse

Skills Required

  • 3+ years of experience in Data Science or Algorithmic Development with Python.
  • Proven ability to translate complex business requirements into code and logical rules.
  • Strong background in Mathematical Optimization, Simulation, or Logic Programming.
  • Fluency in the PyData stack (Pandas, NumPy, SciPy) and SQL.
  • Experience writing production-quality code with modular design and unit testing.
  • Familiarity with orchestration frameworks like Dagster or Airflow (user/logic perspective).
  • BSc/MSc in Mathematics, Physics, Statistics, or Computer Science.
  • Experience in Revenue Management, Air Travel, or Logistics domains.
  • Understanding of Derivative-Free Optimization.
  • Clickhouse
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The Company
200 Employees
Year Founded: 2019

What We Do

Fetcherr is an algo-based company that revolutionizes the travel industry with its groundbreaking Generative Pricing Engine (GPE), the first of its kind to leverage AI for real-time, market-responsive pricing decisions. Our GPE augments airlines' existing pricing strategies with ultra-granular, high-frequency adjustments, fully automating workflows from pricing determination to fare publishing. Operating non-stop, the GPE identifies untapped revenue opportunities and efficiently distributes updated fares across all channels. Partnerships with Virgin Atlantic, Azul, ATPCO, and INFARE attest to our system's unparalleled capability to enhance revenue while streamlining operations.

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