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Algorithm Team Lead – Optimization
Not specifiedFull-timeData EngineeringEnterprise SoftwareArtificial Intelligence
Lead a team of data scientists and data engineers developing the data infrastructure, optimization systems, and machine learning products that support real-time pricing and revenue management decisions.
Responsibilities
- Lead data scientists and data engineers building scalable, high-performance data pipelines and infrastructure.
- Design, build, and maintain distributed batch and streaming data workflows.
- Own and evolve the data architecture in line with product and business goals.
- Establish practices for data quality, validation, testing, and observability.
- Guide architecture decisions, development, deployment, and hands-on implementation of mission-critical systems.
- Manage sprint planning, task breakdown, code reviews, and performance feedback.
- Recruit, mentor, and develop the data science engineering team.
- Support optimization systems that combine demand forecasts, competition, pricing constraints, inventory, and client policies to generate price recommendations.
Requirements
- 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 engineering teams, including people management.
- At least 4 years of data science experience, with strong Python, advanced SQL, and data modeling skills.
- Expertise with Airflow, Prefect, Dagster, or similar data orchestration tools.
- Experience with a cloud platform; GCP is preferred, while AWS or Azure is acceptable.
- Familiarity with Docker.
- Strong communication, mentoring, and collaboration skills.
- BSc or MSc in mathematics, physics, statistics, computer science, or a related field.
- Fluent written and spoken English.
Nice to have
- Experience with Google Cloud tools such as BigQuery, Dataflow, and Pub/Sub.
- Background working with machine learning pipelines or data science teams.
- Knowledge of data contracts, lineage, and versioning tools.
- Understanding of data structures and algorithms.
- Experience improving pipeline and database performance and cost efficiency.
- Experience with CI/CD pipelines using GitHub or GitLab.
- Hands-on experience with Apache Beam, Spark, or similar distributed data frameworks.
- Exposure to airline, pricing, or GDS systems.