EU remote
Data Scientist - Linear Optimization (All Genders)
About this role
As a Data Scientist in Linear and Mixed Integer Optimization, you will join the Resource Planning Team and will contribute to crucial outbound logistics processes and systems in the company. You will have an opportunity to create and enhance tools for cost-efficient planning in a continuously growing logistics network with 1.000.000+ parcels weekly. Here are some things about the way we work: We work in self-organized teams, respecting and valuing everyone´s opinion.
We learn from each other through pair programming, code reviews, and knowledge sharing. We deliver value by developing new features, maintaining existing products and improving the infrastructure required for it, so being cross-functional is part of our DNA. We build quality into our code by following clean code principles and DevOps practices - you build it, you run it. We work in a mature Agile environment, taking a part in entire software development life cycle from discovery through coding, testing, deployment and maintenance.
We continuously grow our skillset staying on top of fast-pacing environment, striving for mastery and using state-of-the-art technologies and practices. We embrace diversity , having colleagues from over 50 countries. This means our working language is English . These are some of the technologies, frameworks, and practices we use: Gurobi, Python Oracle, PostgreSQL, Athena Amazon Web Services and Terraform CI/CD with Jenkins pipelines Docker, Kubernetes Grafana, Kibana Responsibilities: Design, develop and maintain linear optimization and mixed integer models and integrate them in production Analyze data, run simulations, and present actionable insights to stakeholders across engineering, product, and operations.
Contribute to the full SDLC; from ideation and prototyping to deployment, monitoring, and continuous improvement Ensure quality and performance of developed solutions through testing, validation, and monitoring in production. Requirements: BS in Computer Science, Applied Mathematics, or another related field. 3+ years of hands-on experience solving linear optimization and mixed-integer problems 1+ years of experience with commercial solvers (preferably Gurobi) for building and solving optimization models Solid knowledge of advanced mathematical modeling techniques and experience with simulations Proficiency in Python and scientific computing libraries such as Pandas , NumPy , and SciPy .