Senior Data Scientist (m/d/f) at Experian

Düsseldorf, North Rhine-Westphalia, Germany -

Full Time

Start Date

Immediate

Expiry Date

26 Mar, 26

Salary

0.0

Posted On

26 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Analysis, Statistical Methods, Python, SQL, Data Manipulation, Data Engineering, Collaboration, Problem Solving, Communication, Model Validation, Data Products, Analytical Solutions, Business Processes, Risk Management, Data Lakes

Industry

Information Services

Description

Company Description Experian is a global data and technology company that empowers people and businesses around the world. With our unique combination of data, analytics and software, we have established ourselves as one of the leading service providers for risk, fraud and identity management in the DACH region. Experian gives individuals better access to financial services such as loans, insurance, mobile phone contracts and online shopping. We help companies of all sizes and industries make smarter decisions, lend more responsibly and protect themselves and their customers from identity fraud and crime. We invest in our talented people and new, advanced technologies to harness the power of data and drive innovation. We employ 22,500 people in 32 countries and are a FTSE 100 company listed on the London Stock Exchange (EXPN). Our headquarters are in Dublin, Ireland. Job Description The Data Scientist plays a pivotal role in the development and application of advanced analytics and machine learning models to support the development, monitoring, and maintenance of our data products, including Scores, Attributes, and other Data Services. This role is integral to driving innovation and improving the performance of our products, working closely with our Data Engineering, Product & Tech teams ensuring data-driven decision-making. The primary purpose of this role is to develop, implement, and maintain machine learning models and analytical solutions that enhance our data products. It also includes the monitoring of our Bureau Data Asset and the continues improvement of our Bureau Data Ingestion Pipeline. Main focus of this role are product-related tasks with only limited or no involvement in client projects. Main responsibilities, tasks, duties: Develop and implement machine learning models and advanced analytics solutions Monitor the performance and quality of our models and data products Perform ad hoc analyses to support product development and decision-making Collaborate closely with Data Engineering, Product & Tech teams to understand functional requirements and to ensure proper implementation of analytical solutions, new product features and improve processes Ensure model accuracy and integrity through rigorous testing and validation processes Document methodologies, processes, and findings to maintain transparency and reproducibility Extract, manipulate, and analyze data from data lake to support various product development and monitoring activities Support our Legal and Compliance Teams in cases of consumer complaints, questions regarding our Scores and regulatory or policy changes Stay up to date on industry trends and new developments in machine learning and data science Responsibility, e.g. budget, key deliverables: Ensure timely delivery of high-quality machine learning models and analyses Maintain and improve the accuracy and performance of our models and data products Contribute to the development of new product features and enhancements Support data-driven decision making within Product Management Provide insights and recommendations based on data analysis to support strategic decision-making Qualifications Bachelor’s or Master’s degree in data science, Statistics, Computer Science, or a related field Strong analytical and problem-solving skills with keen attention to detail Deep knowledge of statistical methods and machine learning algorithms, especially logistic regression and boosted trees and its application Proficiency in programming languages such as Python or Scala Experience with machine learning frameworks such as XGBoost, PyTorch, or scikit-learn Experience with data manipulation and extraction from data lakes or large data storages using SQL and Spark Proven ability to analyze complex business and risk processes, translating them into actionable data models Preferred further skills (not mandatory): We are not looking for a pure theorist: You should have the ability to interpret and apply analytical models within a business context. Ideally, you have demonstrated how to analyze business processes and translate them into data models to enable data-driven decision-making. Experience in the credit bureau or financial services environment is a plus, but not mandatory Strong ability to communicate complex analytical results clearly and provide actionable insights for non-technical stakeholders Excellent communication and collaboration skills Ability to work independently and manage multiple tasks simultaneously Additional Information What you will get: A high degree of autonomy in a dynamic, internationally oriented organization A motivated team that values innovation and collaboration Great compensation package and attractive employee benefits Flexible working hours and remote work options Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is a critical part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity. #LI-Hybrid Experian Careers - Creating a better tomorrow together Experian Careers - Creating a better tomorrow together Find out what its like to work for Experian by clicking here Employee Status: Regular Role Type: Hybrid Department: Analytics Schedule: Full Time

Responsibilities

The Data Scientist will develop, implement, and maintain machine learning models and analytical solutions to enhance data products. This role also involves monitoring model performance and collaborating with various teams to ensure data-driven decision-making.