Staff Engineer, Machine Learning

Company Description

We are a Digital Product Engineering company that is expanding in a major way! We create products, services, and experiences that inspire, excite, and satisfy. We operate on a large scale — across all devices and digital mediums, with team members located globally (over 15000 experts in 26 countries, to be exact). Our workplace culture is dynamic and non-hierarchical. We are searching for talented new team members. That's where you come in!

Job Description

Essential Skills : Python for Data Science (Advanced), General Experience in Data Science, Machine Learning, Manufacturing & Automation.

Job Description : The Industry and Automation department at Nagarro works with a broad range of industrial clients to achieve their business transformation objectives. We co-develop digital solutions that assist our clients on their path to Industry 4.0. These Industry 4.0 solutions use a range of technologies including Industrial IoT, Cloud, Reality Technologies, Artificial Intelligence, Data Analytics, SAP S/4 Hana, Custom Application, 5G, and more.

We're looking for a technical lead to lead some of our key projects with our clients. Required skills: Python/ Spark/ R, Data Science, problem-solving, Data Science Libraries, machine learning libraries like TensorFlow, Pandas, sci-kit-learn, Keras, TPOT, DataRobot, Hugging Face, h2o.ai and Gurobi Optimization, and others.

The candidate must demonstrate the following skills and experience:

• Proven experience working with Data Science (DS) / Machine Learning (ML) technologies using custom algorithms or data platforms.
• Work experience with SQL and NoSQL databases like MongoDB, Cassandra, Redis, and the like. Experience working with Python/ Spark/ R Data Science Stack. Ability to design and implement Linear & Logistic Regression, Ensemble Models (Random Forest, Boosting, etc.) workflows using Python/ Spark.
• Demonstrable skills in Computational Statistics, Computational Mathematics, ability to use ideas of Data Distributions, Hypothesis Testing, and other Statistical Tests. Experience in operations research and optimization models (timetabling, scheduling, route optimization, etc.).
• Demonstrable skills in sample selection aligned with the Design of Experiments, prompt fine-tuning, zero/one/few-shot learning for model retraining.
• Demonstrable skills in Data Visualization using Python/R, Grafana, Power BI, Tableau, etc.
• Experience in creating data science solutions/ accelerators that result in quality deliverables.
• The candidate should be proficient in the agile delivery model with experience in using an agile product management tool, preferably JIRA.
• Ability to guide the team on DS and ML approaches and technical solutions, perform code reviews, and define integration strategy.
• Effective written and spoken communication skills are vital for global team interaction and client communication.
• Preferably, should have working knowledge of at least 2 cloud hyperscalers out of Azure, AWS and Google Cloud. It would be highly advantageous to have extensive knowledge and practical experience with the implementation and maintenance of production-grade data science pipelines.
• Experience as a technical lead in one or more of the following use case domains would be advantageous: manufacturing, heavy engineering, automotive, consumer goods, food, agriculture, chemicals, building materials, electronics, etc.