👋🏼We're Nagarro.

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at a scale — across all devices and digital mediums, and our people exist everywhere in the world (17500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Responsibilities

• Design, develop, and deploy data science and optimization models into production using APIs, microservices, or cloud platforms (AWS, GCP, Azure).
• Build, automate, and maintain MLOps workflows using tools such as MLflow, Kubeflow, Airflow, or equivalent.
• Apply optimization techniques—including mixed integer programming, heuristic algorithms, and simulation modeling—to solve complex business problems.
• Implement and maintain scalable and modular Python-based solutions following software engineering best practices (version control, testing, CI/CD).
• Collaborate with cross-functional teams including software engineers and UX designers to deliver integrated product solutions.
• Work with optimization solvers and modeling frameworks like Gurobi, CPLEX, Pyomo, or OR-Tools.
• Develop and maintain data pipelines, perform SQL-based data manipulation, and ensure data quality for analytic workflows.
• Apply machine learning fundamentals such as linear models, ensemble methods, clustering, and evaluation techniques to support product and model development.
• Communicate technical concepts, model results, and system implications effectively to both technical and non-technical stakeholders.
• Ensure solutions are scalable, maintainable, and production-ready with a focus on engineering rigor.

Requirements

• Master’s degree (or equivalent experience) in Data Science, Computer Science, Operations Research, Industrial Engineering, or a related quantitative field.
• Strong expertise in Python and software engineering principles including modular coding, testing, version control, and CI/CD.
• Demonstrated experience deploying models through APIs, microservices, or cloud environments (AWS, GCP, Azure).
• Experience building and maintaining MLOps workflows (MLflow, Kubeflow, Airflow, etc.).
• Strong background in optimization and algorithm design (mixed integer programming, heuristics, simulation).
• Familiarity with optimization solvers and modeling tools such as Gurobi, CPLEX, Pyomo, or OR-Tools.
• Proficiency in data engineering concepts including SQL, ETL processes, data modeling, and data quality.
• Solid understanding of statistical learning and ML basics — linear models, ensembles, clustering, evaluation metrics.
• Experience collaborating within cross-functional product teams (engineering, UX, product).
• Excellent written and verbal communication skills for interacting with technical and business stakeholders.
• A mindset focused on scalability, maintainability, and production-quality engineering.

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.