Senior Data Scientist

As a Data Scientist, you will directly contribute to increasing the speed and cost efficiency of NXP’s New Product Introductions. Your work will enable data driven decision making in R&D through high quality insights, automated reporting, and scalable analytics products.

Working closely with data engineers and data scientists, you will help define the future of R&D analytics at NXP. You build robust, automated, and user friendly dashboards and reports that empower our R&D community with self service business intelligence capabilities.

As part of the Hardware Design Analytics team, you will innovate and evolve the analytics products that support our R&D organization. You will have plenty of room for new ideas, experimentation, and technology improvements collaboration is at the core of how we work.

• →Stakeholder Collaboration: Work with project managers, resource managers, IT teams, and other stakeholders to gather requirements, define project scope, and ensure alignment with business objectives.
• →Data Analysis: Collect, analyze, and interpret datasets from R&D projects to uncover trends, key performance indicators, risks, and opportunities. Translate complex data into meaningful business insights through reliable, high quality visualizations and clear analytical storytelling.
• →Dashboarding & Reporting: Design, develop, and maintain powerful and trustworthy dashboards and automated reports using Python. Ensure that visualizations clearly communicate insights and support impactful decision making.  Gather user feedback and iterate to continuously improve usability and impact.
• →Machine Learning & AI Development: Build and deploy ML models (e.g., forecasting, NLP, optimization, automation) to improve R&D efficiency and quality. Ensure proper evaluation, explain ability, and production monitoring.
• →Data Engineering Support: Collaborate with data engineers to improve data pipelines, data quality, and data models used for reporting and analytical products.
• →Automation & DevOps: Build analytics solutions with a DevOps mindset ensure reproducibility, automation, and quality by leveraging CI/CD pipelines, version control, and modern development practices.

You can describe yourself as follows:

• Education: A master’s degree in Business Intelligence, Data Engineering, Data Science, Software Engineering, Computer Science, or a related field.
• Experience: 3+ years of experience as a Data Scientist, preferably within a complex IT or R&D environment.

• Coding: Strong proficiency in Python and SQL, including experience working with data processing libraries and frameworks. Hands on experience with Shiny, Plotly and other python visualization packages is a big plus.
• Visualization: Experience building dashboards and reports, and a passion for data visualization and user‑centric design.
• Machine Learning: Experience in ML and AI frameworks (e.g., scikit‑learn, PyTorch, TensorFlow, XGBoost).
• Automation: A strong interest in automation, cloud technologies, Infrastructure as Code (preferably using CDK), DevOps practices, and CI/CD pipelines (preferably using Gitlab).

• Strategic Problem-Solving: Comfortable owning technical challenges and designing long term, scalable solutions.
• Customer & Stakeholder Focus: Strong communicator who can translate technical concepts into business value and collaborate effectively across data science, architecture, and wider R&D.
• Team Mindset: A natural collaborator who contributes to an open, supportive working culture
• Agile & Scrum: Experienced working in Agile environments, actively participating in sprints, stand ups, and iterative delivery cycles to ensure continuous improvement and timely value delivery.

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