Data Science & AI Specialist

At Uni Systems, we are working towards turning digital visions into reality. We are continuously growing and we are looking for a Data Science & AI Specialist to join our UniQue team.

• Design, develop and implement end-to-end Data Science, AI, Machine Learning and data visualisation solutions.
• Translate business needs into technical requirements, user stories and measurable analytical objectives.
• Develop, validate, test and optimise predictive, statistical and machine learning models.
• Design and manage prototypes, proof-of-concepts and AI/ML solution deployments.
• Apply MLOps and DevOps practices, including model versioning, automated pipelines, testing, monitoring and lifecycle management.
• Establish and maintain technical standards, methodologies, documentation and reusable components for Data Science and AI solutions.
• Evaluate model performance, accuracy, reliability and business impact.
• Collaborate with business stakeholders, product owners, data engineers and technical teams throughout the solution lifecycle.
• Facilitate workshops and Design Thinking sessions to identify opportunities for AI and Advanced Analytics.
• Contribute to responsible AI practices, model governance, quality assurance and continuous improvement.
• Support knowledge sharing and the development of Data Science and AI capabilities across the organisation.

• Master's degree in IT or a related field and at least 8 years of relevant experience in Data Science, AI, ML.
• At least two of the following professional certifications: Certified Analytics Professional (CAP), CDP Data Engineer, CDP Data Analyst, Microsoft Certified: Azure Data Scientist Associate.
• Proven experience in designing and implementing end-to-end Data Science and Machine Learning solutions, covering data preparation, feature engineering, model development, validation, deployment and monitoring.
• Strong practical knowledge of Python and relevant Data Science and ML frameworks, such as pandas, scikit-learn, PyTorch, TensorFlow, MLflow and Spark/PySpark.
• Experience with cloud-based AI/ML platforms, preferably Microsoft Azure, including Azure Machine Learning, Azure AI Foundry and Azure OpenAI, or equivalent technologies.
• Practical experience with MLOps, DevOps, CI/CD, model registries, automated testing and reproducible data pipelines.
• Knowledge of advanced analytics and AI use cases, including predictive analytics, forecasting, anomaly detection, NLP, computer vision and Generative AI.
• Experience working with structured and unstructured data, relational and NoSQL databases, APIs and large-scale data platforms.
• Understanding of data engineering, data quality, data governance and data visualisation techniques and tools.
• Knowledge of containerisation and deployment technologies such as Docker and Kubernetes, including hybrid, on-premises or restricted environments.
• Ability to translate complex business challenges into practical technical solutions and communicate results effectively to technical and non-technical stakeholders.
• Understanding of Responsible AI, model explainability, bias, data protection and AI governance.
• Familiarity with Data Science methodologies such as CRISP-DM or TDSP.
• Experience contributing to or developing enterprise-wide Data Science, AI or Advanced Analytics capabilities is considered an advantage.
• Experience with real-time analytics, predictive maintenance, recommendation systems, forecasting and image/video analytics is considered an advantage.
• Experience in regulated, public-sector or secure IT environments, including isolated or air-gapped infrastructures, is considered an advantage.
• Advanced English (C1) communication skills (written and spoken).

At Uni Systems, we are providing equal employment opportunities and banning any form of discrimination on grounds of gender, religion, race, color, nationality, disability, social class, political beliefs, age, marital status, sexual orientation or any other characteristics. Take a look at our Diversity, Equality & Inclusion Policy for more information.