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Data Science Team Lead
PresencialTiempo completoData ScienceEnterprise Software
Lead a team of data scientists and data engineers building scalable data infrastructure, distributed processing workflows, and machine learning products for real-time pricing and decision intelligence.
Responsabilidades
- Manage a team of data scientists and data engineers.
- Build and maintain scalable, high-performance data pipelines and infrastructure.
- Design and maintain distributed batch and streaming data processing workflows.
- Establish practices for data quality, validation, testing, and observability.
- Own and evolve data architecture in alignment with business and product goals.
- Lead sprint planning, task breakdown, code reviews, and performance feedback.
- Contribute hands-on to development work and architecture decisions.
- Recruit, mentor, and develop the data science engineering team.
Requisitos
- Proven experience as a data scientist.
- Experience designing and maintaining large-scale data platforms handling hundreds of terabytes.
- At least 3 years of experience leading and managing data engineers, including people management.
- At least 4 years of data science experience.
- Strong Python programming, advanced SQL, and data modeling skills.
- Expertise with Airflow, Prefect, or Dagster.
- Experience with a cloud platform; GCP is preferred, with AWS or Azure also accepted.
- Familiarity with Docker.
- Bachelor’s or master’s degree in mathematics, physics, statistics, computer science, or a related field.
- Fluent spoken and written English.
Se valora
- Experience with Google Cloud Platform tools such as BigQuery, Dataflow, and 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.
- Experience with CI/CD pipelines using GitHub or GitLab.
- Hands-on experience with distributed data frameworks such as Apache Beam or Spark.
- Exposure to airline, pricing, or GDS systems.