Data Analyst

At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.

Why you should join:

We are seeking a highly analytical and proactive Data Analyst to support our Research & Development initiatives and financial planning efforts. This role is pivotal in enabling data-driven decisions across innovation projects, operational forecasting, and strategic investment analysis. You will collaborate closely with engineering, finance, and project management teams to deliver insights that shape the future of our R&D portfolio.

Responsibilities :

• Analyse R&D project data to identify trends, risks, and opportunities for optimisation.
• Support financial modelling and cost-benefit analysis for ongoing and proposed R&D initiatives.
• Develop and maintain forecasting models to improve accuracy in resource planning and budget allocation.
• Create dashboards and reports that communicate project performance, financial health, and operational efficiency.
• Maintain and update master data in systems such as IBP/SAP, ensuring alignment with project and financial metrics.
• Collaborate with cross-functional teams to ensure data integrity and actionable insights across engineering and finance domains.

Desired Candidate profile:

• Bachelor’s degree in Data Science, Finance, Engineering, or a related field.
• Minimum 3 years of experience in data analysis, preferably within R&D or financial environments.
• Strong proficiency in Excel, ERP systems, and SAP.
• Experience with financial analysis tools and techniques.
• Excellent analytical and problem-solving skills.
• Ability to communicate complex data clearly to technical and non-technical stakeholders

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Preferred Skills:

• Familiarity with project lifecycle management and R&D metrics.
• Experience in supporting investment decisions and ROI analysis.
• Knowledge of data quality tools such Tableau, Power BI etc.
• Exposure to machine learning workflows and human-in-the-loop feedback processes.