Data Science Team Lead

Fetcherr is an AI-driven company specializing in deep learning, algorithmic trading, and large-scale data solutions. Our core technology, the Large Market Model (LMM), enables accurate demand forecasting and real-time, data-driven decision-making. Originally focused on the airline industry, Fetcherr is expanding its AI solutions across additional industries.

We are seeking an experienced Data Science Team Lead to lead our data science and data engineering efforts and oversee a team of skilled data engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power real-time pricing, large-scale data pipelines, and machine learning products.

You will lead the team through architecture decisions, development, and deployment of mission-critical systems—while growing and mentoring a high-performing team.

Responsibilities

Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure.

Design, build, and maintain distributed data processing workflows (batch & streaming).

Drive best practices for data quality, validation, testing, and observability.

Own and evolve Fetcherr’s data architecture in alignment with business and product goals.

Manage sprint planning, task breakdown, code reviews, and performance feedback for your team.

Contribute hands-on to key development tasks and architecture decisions.

Recruit, mentor, and grow the data engineering team.

Requirements:

Proven experience designing and maintaining large-scale data platforms (hundreds of TBs)

3+ years of proven experience leading and managing a team of data engineers (people management is required)

4+ years of experience in data science, including a strong Python programming background, advanced SQL skills, and data modeling experience

Expertise with data orchestration tools (Airflow, Prefect, or Dagster)

Cloud platform experience — GCP preferred (AWS/Azure acceptable)

Familiarity with Docker

Strong communication, mentorship, and collaboration skills

BSc/MSc in Mathematics/ physics/ statistics/ Computer Science.

Fluent English (spoken and written)

Bonus Points:

Experience with Google Cloud Platform tools (BigQuery, Dataflow, Pub/Sub)

Background working with ML pipelines or data science teams

Understanding of data contracts, lineage, and versioning tools

Knowledge of data structures and algorithms

Experience optimizing pipelines and databases for performance and cost

CI/CD pipelines (GitHub/GitLab)

Hands-on experience with distributed data frameworks (Apache Beam, Spark, or similar)

Exposure to airline, pricing, or GDS systems

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