Data Scientist 2

Overview

As an Analytics Engineer within the R&D Engineering organization, you will standardize, integrate, and automate engineering data and data management practices across mechanical, electrical, hardware, and firmware engineering teams. You will transform multidisciplinary data into scalable analytics, business intelligence, and AI solutions that support product development in a regulated medical device environment.

What you'll do

• Lead efforts to standardize and automate engineering data pipelines across mechanical, electrical, hardware, and firmware domains.
• Design, model, and integrate structured and unstructured data from multiple engineering and enterprise systems.
• Build and maintain business intelligence dashboards and analytics using tools such as Power BI and Tableau.
• Translate complex technical data into actionable insights for R&D and leadership through visualizations and executive-level reporting.
• Partner with engineering and IT stakeholders to define data governance, data quality standards, and scalable data management practices.
• Write and maintain queries, transformations, and automations using SQL and related programming languages.
• Support data modeling and storage solutions using platforms such as MongoDB and relational databases.
• Drive the evaluation, pilot, and implementation of AI solutions, including custom models and third-party platforms.
• Analyze and interpret engineering test and validation data using statistical methods to identify trends, variability, and performance drivers across products and systems.
• Develop statistical models and summaries to support engineering decision-making, trade studies, and design verification activities.
• Collaborate cross-functionally to identify opportunities where data analytics and AI can improve engineering processes, quality, and decision-making.

What you'll need

• Proven experience in a data analyst or data scientist role supporting engineering, R&D, or technical organizations.
• A Bachelor’s degree in a technical discipline and a minimum of 3-5 years related experience, or a Master’s degree and 2 years equivalent industry experience, or a PhD and 0-2 years experience.
• Strong experience developing dashboards and analytics in Power BI and/or Tableau.
• Comfort programming for data integration, automation, and analytics workflows.
• Understanding of engineering data types and workflows across mechanical, electrical, hardware, and firmware development.
• Experience deploying or supporting AI and machine learning solutions, including integration of third-party AI tools.
• Ability to communicate clearly and effectively while collaborating with engineers, data consumers, and leadership.
• Ability to manage multiple data initiatives in a fast-paced, regulated environment.
• An eye for process improvement, with an interest in standardization, efficiency gains, and opportunities for automation within engineering workflows.

Nice to have

• Proficiency in data modeling, querying, and transformation using SQL and NoSQL technologies such as MongoDB.
• Experience with Onshape, especially in environments transitioning from traditional CAD tools.
• Exposure to CAD data migration or platform adoption efforts.

Details

• Location: Bengaluru, India.
• Travel required: 0-5%.