Staff Engineer, Machine Learning

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 scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 26 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!

Must have Skills : Python for Data Science (Strong), Data Science - General Experience, Machine Learning - General Experience, Manufacturing & Automation - General Experience

Job Description : The Industry and Automation Practice at Nagarro is responsible for working with a wide range of industrial clients to enable their business transformation goals. We help co-create digital solutions that assist our clients in their Industry 4.0 journey. These Industry 4.0 solutions leverage diverse technologies such as Industrial IoT, Cloud, Reality Technologies, Artificial Intelligence, Data Analytics, SAP S/4 Hana, Custom Application, 5G, and more.

We are looking for a technical lead to steer some of our key initiatives with clients: Mandatory skills: Python/ Spark/ R, data science, problem-solving, libraries for data science, machine learning libraries like TensorFlow, Pandas, sci-kit-learn, Keras, TPOT, DataRobot, Hugging Face, h2o.ai and Gurobi Optimization, etc.

The candidate must demonstrate the following skills and experience:

• Demonstrated experience of working on Data Science (DS) / ML (Machine Learning) technologies using custom algorithms or data platforms.
• Working experience with SQL and NoSQL databases like MongoDB, Cassandra, Redis, etc. Working experience with Python/ Spark/ R Data Science Stack. Ability to design and implement workflows of Linear & Logistic Regression, Ensemble Models (Random Forest, Boosting, etc.) using Python/ Spark.
• Demonstrable competency 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 competency in sample selection aligning to the Design of Experiments, prompt fine-tuning, zero/ one/few-shot learning for model uptraining.
• Demonstrable competency in Data Visualization using Python/R, Grafana, Power BI, Tableau, etc.
• Experience in creating data science solutions/ accelerators leading to quality deliveries.
• Candidate should be fluent in the agile delivery model with experience in working with any of the an agile product management tool, preferably JIRA.
• Ability to guide the team on DS and ML approaches, and technical solutions, perform code review, and define integration strategy.
• Effective written and verbal communication skills are essential to communicate in a global team and with clients
• Preferable to have a working knowledge of at least 2 cloud hyperscaler out of Azure, AWS and Google Cloud. It is highly desirable to have extensive knowledge and hands-on experience with the implementation and maintenance of production-grade data science pipelines.
• It would be advantageous to have experience as a technical lead while working in one or more of the following use case domains: manufacturing, heavy engineering, automotive, consumer goods, food, agriculture, chemicals, agriculture, building materials, electronics, etc.