We are the leading global information services company, providing data and analytical tools to our clients around the world. We help businesses to manage credit risk, prevent fraud, target marketing offers and automate decision making. We also help people to check their credit report and credit score and protect against identity theft.
We employ approximately 17,400 people in 44 countries and our corporate headquarters are in Dublin, Ireland, with operational headquarters in Nottingham, UK; California, US; and São Paulo, Brazil.
Experian is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status.
We are committed to building an inclusive culture and creating an environment where people can balance successful careers with their commitments and interests outside of work. Our flexible working practices support our belief that this balance brings long-lasting benefits for our business as well as our people. Some roles lend themselves to flexible options more than others, and if this is important to you, we are open to discussing agile working opportunities during the hiring process.
We’re currently looking for an Associate ML Engineer – Ascend Intelligence Services (AIS) to join the EMEA Analytics Product Development Team. Ascend Intelligence Services™ is Experian’s cloud-based end-to-end platform, designed to scale and democratize machine learning and empower lenders of all sizes with Experian’s advanced data and analytics capabilities. You would be part of the team responsible for automating and streamlining the development, continuous retraining, deployment and monitoring of sophisticated models and strategies to predict risk and gauge portfolio health. If you are passionate about crafting the next generation of analytics products and services, using your engineering and programming skills to solve diverse MLOps challenges, we could be a great place for you to work.
- Support product development by creating new features and automating processes in AIS or stand-alone analytics products
- Produce high-quality clean, testable, and efficient code
- Document new services and features
- Investigate production issues, recreating problems and utilizing trace files & error diagnostics. Identify root cause and propose solutions.
- Support our analytics team members to ensure accuracy and operational feasibility of solutions, from solution design through on-boarding and implementation
- University degree in a related quantitative field (Data Science, Computer Science, Math, Statistics, Engineering, Physics, or related discipline).
- Demonstrated experience with Python and knowledge of OOP principles, data structures, algorithms & design patterns
- Exposure to statistical analysis, applying various machine learning techniques, predictive modeling, and data mining to interpret data and solve business problems
- Ability to think creatively, solve problems, learn quickly, handle ambiguity, and adapt to change in a fast-paced environment
- Ability to communicate ideas and results effectively both verbally and in writing, to both a technical and non-technical audience (fluency in English)
Any of the following abilities and skills will be considered an advantage:
- Knowledge and appreciation of agile development methodologies and techniques
- Experience with data querying languages (e.g. SparkSQL)
- Familiarity in using AWS, PySpark, Java, Scala, Spark, and data visualization tools
- Personal Development – career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials & books
- Work environment – excellent work conditions with friendly environment, recognized strong team spirit, and fun and quality recreation time
- Social benefit package – life insurance, food vouchers, additional health insurance, corporate discounts, Multisport card, and a Share options scheme
- Work-life balance – 25 days paid vacation and 3 additional paid days for participation in Social responsibility events
- Opportunity for Flexible working hours and Home Office
In order to stay safe and be responsible, we introduce a remote hiring process with online interviews for all candidates.