Company Description
Experian is a global data and technology company that opens up new possibilities for people and businesses around the world. With our unique combination of data, analytics, and software, we help redefine credit decision practices, uncover and prevent fraud, simplify healthcare, develop marketing solutions, and gain deeper insights into the automotive market. We also support millions of people in achieving their financial goals and saving time and money.
We operate in a variety of markets, including financial services, healthcare, automotive, agriculture, insurance, and many other industries.
We invest in people and new technologies to unlock the full potential of data. As an FTSE 100 company listed on the London Stock Exchange (EXPN), we employ 22,500 employees in 32 countries. Our corporate headquarters is located in Dublin, Ireland. For more information, visit experianplc.com.
Job Description
We are looking for a Senior Data Analyst Insurance (m/f/d) with experience in the insurance industry for our Customer Analytics team, which creates data-driven solutions for our customers. This position is critical to delivering meaningful analytics, supporting pre-sales activities, and driving innovation in areas such as credit risk, fraud detection, and customer intelligence. The Senior Consultant (m/f/d) combines technical expertise with business acumen and ensures that our customers derive measurable value from Experian's local and regional data products and analytics services. This position offers the flexibility to work with our offices in Düsseldorf or Frankfurt in a hybrid work model.
Main responsibilities
- Analyze large, diverse datasets to derive actionable insights that support business decisions in credit risk, fraud analysis, and customer behavior
- Design, develop, and implement advanced statistical models and machine learning solutions for complex customer challenges
- Drive pre-sales activities: assess customer needs, develop tailored solution concepts, and support proof-of-concept projects
- Work closely with cross-functional teams – including sales, product development, and marketing – to ensure seamless integration of analytics into customer solutions
- Deepen customer relationships, identify new business opportunities, and support business development initiatives
Qualifications
· Bachelor's degree in mathematics, statistics, data science, computer science, or a related field
· Several years of practical experience in data analysis, analytics, or consulting, ideally with a focus on credit risk, fraud analytics, or marketing analytics
· Sound knowledge of requirements and analytical use cases in an area of the insurance industry
· Demonstrated expertise in statistical modeling, machine learning, and data mining; knowledge of Python or similar programming languages and Pyspark
· Experience with cloud-based data and analytics platforms as well as data visualization tools is advantageous
· Fluent German and English language skills
Additional Information
Our uniqueness lies in celebrating your uniqueness. Experian's culture and employees are key differentiators. We take our people agenda very seriously and focus on what matters: DEI, work-life balance, development, authenticity, collaboration, wellbeing, reward and recognition, volunteering ... the list goes on. Experian's employee-centric approach has been recognized multiple times, including the awards "World's Best Workplaces™ 2025" (Fortune Top 25) and "Great Place To Work™" in 26 countries. Visit Experian Life on social media or our careers page to find out why.
Experian is proud to be an equal opportunity and equal treatment employer. Innovation is a key part of Experian's DNA and practices, and our diverse workforce is the engine of our success. At Experian, everyone can succeed and fully contribute, regardless of gender, ethnicity, religion, skin color, sexuality, physical abilities, or age. If you have a disability or special needs that require accommodation, please let us know as early as possible.
Experian Careers - Creating a better tomorrow together
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