Summary:
Join Data & Analytics as Data Scientist and help build the next generation of data and AI-driven solutions.
Job Description:
What will you do?
This role sits at the intersection of business, data engineering, and AI innovation, where you will translate business problems into scalable data and AI use cases.
You will play a key role in designing, developing, deploying, and maintaining statistical (credit risk) models and AI solutions, with a strong focus on Databricks and modern cloud platforms (Azure).
Beyond traditional data science, you will actively contribute to AI solution design, leveraging tools such as Azure AI Foundry, LangChain, and LangGraph, enabling the business to unlock value through cutting-edge AI capabilities.
Responsibilities
1. Data Science & Modelling
- Develop, deploy, and maintain statistical and machine learning models;
- Ensure models are production-ready, explainable, and compliant;
- Apply best practices in experimentation, validation, and testing;
- Build and maintain solutions on Databricks, including pipelines and model deployment workflows;
- Implement MLOps best practices to ensure scalability, reliability, and monitoring;
- Collaborate with engineers to integrate models into the enterprise data platform.
2. AI & Advanced Analytics
- Design and develop AI solutions using frameworks such as LangChain and LangGraph;
- Work with Azure AI Foundry to build and operationalize AI use cases;
- Translate business problems into technical AI solutions (know where to use AI and where not to);
- Enable business teams with intelligent, scalable, and practical AI implementations.
3. Quality & Engineering Excellence
- Treat testing as an integral part of development, including unit, integration, and data validation tests;
- Ensure high-quality, production-grade code and solutions;
- Maintain robust documentation for models, pipelines, and processes.
4. Collaboration & Architecture
- Work closely with business stakeholders, data engineers, and architects;
- Support architecture discussions by contributing best practices and technical insights;
- Ensure solutions align with enterprise architecture and governance standards.
Your Team
You will be part of the Advanced Analytics team, a multidisciplinary team within the Data & Analytics department. The team’s mission is to enable the organization to deliver high-quality, scalable AI & data products using a modern cloud & data platform.
We work closely with domain teams across risk, retail, corporate banking, and finance to drive target="_blank">here).
What do you bring?
- Bachelor’s or Master’s degree in Data Science, Computer Science, or a related field;
- 5+ years of experience in Data Science, AI, or MLOps roles;
- Proven experience in developing, deploying, and maintaining statistical and machine learning models;
- Strong proficiency in Python, with experience writing production-grade code;
- Experience with Spark is a pre;
- Hands-on experience with Databricks, including model development, jobs, pipeline orchestration, and deployment workflows;
- Experience working with cloud platforms (preferably Azure) and modern data architecture.
We are looking for someone who:
- Has a “can-do” mentality and focuses on solutions rather than problems;
- Takes ownership of quality and does not compromise on deliverables;
- Treat testing and validation as core responsibilities;
- Is a strong team player, collaborating effectively across teams;
- Communicates clearly with both technical and non-technical stakeholders;
- Thinks proactively about innovation and continuous improvement;
- Embraces AI and continuously finds ways to enhance personal and team productivity.
Still intrigued?
Click the apply button now! To upload multiple documents, click the upload button again after uploading a document. An assessment may be part of the application procedure. For more information about the recruitment procedure or NIBC as employer you may contact our HR Servicedesk via AskHR@nibc.com
Applications via email will not be taken into consideration.
