Senior Data Scientist - R&D Analytics

About the role

NXP is looking for a Senior Data Scientist in Bangalore to join its Hardware Design Analytics team. The role helps increase the speed and cost efficiency of NXP's New Product Introductions by enabling data-driven decisions in R&D through high-quality insights, automated reporting and scalable analytics products. You will work closely with data engineers and data scientists to build robust, automated and user-friendly dashboards and reports that give the R&D community self-service business intelligence.

Key responsibilities

• Work with project managers, resource managers, IT teams and other stakeholders to gather requirements, define project scope and align with business objectives.
• Collect, analyze and interpret R&D datasets to find trends, KPIs, risks and opportunities, turning them into clear visualizations and business insights.
• Design, develop and maintain dashboards and automated reports in Python, gathering user feedback and iterating on usability.
• Build and deploy machine learning models (forecasting, NLP, optimization, automation) with proper evaluation, explainability and production monitoring.
• Collaborate with data engineers to improve data pipelines, data quality and data models.
• Build analytics solutions with a DevOps mindset, using CI/CD pipelines, version control and modern development practices.

Required profile

• Master's degree in Business Intelligence, Data Engineering, Data Science, Software Engineering, Computer Science or a related field.
• 3+ years of experience as a Data Scientist, preferably in a complex IT or R&D environment.
• Experience in Agile environments, taking part in sprints, stand-ups and iterative delivery.
• Strong communicator who can translate technical concepts into business value and works well across data science, architecture and R&D.

Required skills

• Python and SQL, including data processing libraries and frameworks.
• Dashboards and reports, with Shiny, Plotly and other Python visualization packages a big plus.
• Machine learning frameworks such as scikit-learn, PyTorch, TensorFlow and XGBoost.
• Interest in automation, cloud technologies, Infrastructure as Code (preferably CDK), DevOps and CI/CD (preferably GitLab).