Data Scientist

We are looking for a talented, motivated Data Scientist to join our dynamic team. As a Data Scientist, you will leverage your analytical skills and expertise in machine learning, reporting, dashboard and KPI to extract insights from complex datasets and drive data-driven decision-making across our organization. You will collaborate closely with cross-functional teams to develop predictive models, uncover actionable insights, build up reports and dashboards, and solve challenging business problems.

Job Description

In your new role you will:

• Collect, process, and analyze large datasets from various sources, including manufacturing, testing, and customer feedback
• Map, produce, transform, and test new data feeds for data owners and consumers, selecting the most appropriate tools and technologies. Conduct ad hoc data exploration in common data serialization and storage formats used across the business for consumers.
• Develop, code, test, correct, and document simple programs or scripts under the direction of others as part of a multidisciplinary team. You can maintain databases, data warehouses, and data visualization tools to support data analysis and reporting
• Identify trends, patterns, and correlations in data to inform quality improvement initiatives and defect reduction strategies
• Create data-driven reports, dashboards, and visualizations to communicate insights and recommendations to stakeholders, including quality engineers, manufacturing teams, and senior leadership
• Proactively explore areas of innovation. You can identify the business value for innovation within your team
• Collaborate with cross-functional teams to design and implement data-driven solutions to improve product quality and reduce defects
• Develop and maintain data quality metrics and KPIs to measure performance and track progress
• Stay up to date with industry trends, best practices, and emerging technologies in data analysis and visualization
• Provide training and support to team members on data analysis tools and techniques
  
  

Your Profile

You are best equipped for this task if you have:

• Bachelor’s degree or master’s degree in computer science, Statistics, Mathematics, or a related field
• Preferred at least one to two years of experience in data analysis, preferably in semiconductor area or in manufacturing or quality-related environment
• Strong understanding of statistical analysis, hypothesis testing, and experimental design.
• Experience with machine learning libraries and frameworks
• Strong proficiency in data analysis tools, such as Python, R, or SQL, and data visualization tools, such as Tableau, Power BI, or D3.js
• ML Models development and approaching
• Excellent analytical, problem-solving, and communication skills
• Ability to work with large datasets and perform statistical analysis, data mining, and data modeling
• Strong understanding of data quality principles and data governance practices
• Experience with data warehousing, ETL, and database management systems
• Ability to work in a fast-paced environment and meet deadlines
• Strong collaboration and teamwork skills
  
  

#WeAreIn for driving decarbonization and digitalization.

As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener.

Are you in?

We are on a journey to create the best Infineon for everyone.

This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant´s experience and skills.

Please let your recruiter know if they need to pay special attention to something in order to enable your participation in the interview process.