Staff Engineer (Data Science - Data Modeling, Operations Research,Optimizat at Nagarro

, , India -

Full Time

Start Date

Immediate

Expiry Date

23 Feb, 26

Salary

0.0

Posted On

25 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Optimization, Python, MLOps, APIs, Cloud Platforms, SQL, Machine Learning, Statistical Learning, Cross-Functional Collaboration, Software Engineering, Data Engineering, Version Control, Testing, CI/CD, Algorithm Design

Industry

IT Services and IT Consulting

Description

Company Description 👋🏼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! Job Description 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. Qualifications Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

Responsibilities

Design, develop, and deploy data science and optimization models into production while collaborating with cross-functional teams. Build and maintain MLOps workflows and ensure solutions are scalable and production-ready.