Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.
Our Experian Software Solution's Analytics Services Team supports advanced analytic and generative AI products for decisioning, analytics, fraud, and identity globally.
As a Machine Learning Engineer, you will design, build, and deploy cutting‑edge machine learning and generative AI solutions at scale. You will combine deep data science expertise with ML engineering and data engineering capabilities to deliver production‑ready models, prototypes, and platform capabilities. You will also partner with cross‑functional teams to support new global product launches, client implementations, and early client adoption. You will report to the Director of Data Science and Gen AI.
What you'll do:
- You will partner with data scientists and then expand to cover packaging and productization of additional analytics solutions.
- You would deliver the last mile of those innovations, ensuring that production code is executed within the Ascend platform and software that Experian delivers to clients.
- Craft advanced machine learning analytical solutions and prototypes to extract insights from diverse structured and unstructured data sources. Articulate model processes and outcomes, documenting and presenting findings and performance metrics, and translating complex findings into relevant insights.
- Use Gen AI and model development tools to develop new models and to prototype and deploy new generative capabilities, including prompt engineering, fine‑tuning, RAG, and model evaluation frameworks.
- Develop production-quality code following software engineering best practices, including modular design, version control, code reviews, and automated testing, ensuring reliability and reproducibility.
- Design and implement advanced algorithms to solve complex challenges, exploring methods across supervised, unsupervised, deep learning, graph analytics, anomaly detection, and reinforcement learning.
What we're looking for:
- 4+ years of experience in AI, data science, or predictive modeling, with a track record for managing complex, hands-on analytical technology, innovation, and client-focused projects;
- Advanced degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field;
- Statistical modeling proficiency in at least one programming language, with coding skills in Python,and proficiency with distributed computing frameworks (AWS). Experience with large data analysis using Spark (pySpark preferred) and model development using Python or SAS;
- Experience applying Generative AI-based tools and rapid prototyping of new concepts;
- Having some background in model risk management / governance processes, regulatory requirements, and LLM advances.
You will get:
- Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and books.
- Work environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time.
- Social benefit package including life insurance, food vouchers, additional health insurance, monthly flex allowance and internet coverage, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits!
- Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event.
- Opportunity for Flexible working hours and Home Office.
Experian is an Equal opportunity employer. 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.
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