À propos
Join a globally recognised organisation driving innovation in data, security, and advanced analytics. Known for its very solid team, low attrition, and nice environment to work in, the company offers an excellent salary package, great benefits, and very good career progression. It’s a place where people stay long-term and benefit from a very good team environment.
Is this the role you are looking for If so read on for more details, and make sure to apply today.
The Opportunity
We are seeking a hands‑on Data Scientist with strong expertise in Machine Learning, Deep Learning, and Generative AI. This role focuses on designing and deploying scalable AI solutions, while also supporting modern data platforms that enable advanced analytics.
You will work on high‑impact use cases such as risk modelling and intelligent automation, collaborating with cross‑functional teams to deliver production‑ready solutions.
Key Responsibilities- Translate complex business challenges into data‑driven solutions using ML, DL, and GenAI techniques
- Manage the full model lifecycle including data exploration, feature engineering, modelling, validation, and deployment
- Build classification and scoring models, effectively handling incomplete or ambiguous datasets
- Develop explainable AI outputs to support business decision‑making
- Deploy and monitor models to ensure performance, scalability, and reliability
- Prototype new concepts and evaluate emerging tools and frameworks
- Collaborate with engineering and product teams to deliver scalable, production‑ready systems
- Support data pipelines, cloud platforms, and CI/CD processes for analytics workloads
- Proven experience delivering end‑to‑end ML and DL solutions in production environments
- 8+ years commercial experience
- Strong programming skills in Python and solid SQL expertise
- Experience with xcfaprz Generative AI, including LLMs, RAG, vector databases, and agent‑based frameworks
- Strong analytical thinking with the ability to communicate insights to both technical and non‑technical stakeholders
- Hands‑on experience in data preparation, feature engineering, and model evaluation
- A proactive and solution‑oriented mindset, comfortable working in fast‑paced environments
- Experience in fraud, risk, or security analytics
- Exposure to model governance, explainability, and regulated environments
- Familiarity with cloud‑based data platforms and large‑scale data processing
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Compétences linguistiques
- English
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