Senior ML Data Scientist - Remote
Company Description
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to work towards their financial goals and help them save time and money.
We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.
We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.
Job Description
Experian's commercial division of Machine Learning and Advanced Analytics team is looking for a Data Scientist to support internal and external credit modeling projects. Reporting to the Sr Manager ML and Advanced Analytics, Commercial Data Sciences, you'll work with analytics consultants, external clients, and other project team members to lead modeling projects from beginning to implementation.
Responsibilities
- Lead end-to-end development of credit risk models, including data sampling, feature engineering, model training, testing, and performance monitoring.
- Collaborate with internal consultants in developing custom client credit risk or fraud models.
- Support internal generic score and external client validations
- Partner with technology teams to bring models to production
- Architect and implement LLM-based agents can tool use, memory, and multi-step reasoning.
- Integrate agents with internal APIs, databases, and third-party services to promote dynamic decision-making and task execution.
- Monitor, evaluate, and improve on agent performance using structured evaluation frameworks.
Qualifications
- 3+ years of experience in machine learning, NLP, or predictive modeling
- Model development experience using Logistic Regression and ML methods such as Gradient Boosting
- Proficiency in Python is a must
- Experience with commercial and consumer credit data
- You have some experience building RAG pipelines, LLM agents using OpenAI functions and GenAI frameworks (e.g., LangChain, Haystack), along with familiarity with orchestration tools and cloud platforms to support scalable and efficient deployment
Additional Information
- Great compensation package and bonus plan
- Core benefits including medical, dental, vision, and matching 401K
- Flexible work environment, ability to work remote, hybrid or in-office
- Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
- Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html
At Experian, our people and culture set us apart. We're committed to creating an environment where everyone feels they belong and can excel. From inclusion and authenticity to work/life balance, development, wellness, collaboration, and recognition, we focus on what matters. Our people-first approach has earned us global recognition: World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ 2025 in 26 countries, and Glassdoor Best Places to Work 2024, among others.
Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important 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.
Want to see what life at Experian is really like? Explore Experian Life on social or visit our Careers Site.
Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related experience, and education. You will be also eligible for a variable pay opportunity and a comprehensive benefits package.
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