Data Scientist (Senior)
Full-time
Sabenza IT & Recruitment
The Senior Data Scientist will be responsible for translating business problems into data-driven and AI-enabled solutions. The role requires strong expertise in data analysis, machine learning, data engineering, and stakeholder engagement, while working closely with data engineering, AI platform, and observability teams.
Key Responsibilities
- Translate business problems into data-driven and AI-enabled solutions
- Perform exploratory data analysis to uncover patterns, issues, and opportunities
- Design, build, and maintain data pipelines to support analytics and modelling use cases
- Develop, train, evaluate, and iterate on machine learning and AI models
- Apply appropriate model evaluation techniques and define success metrics
- Support operational data workflows and resolve day-to-day data processing issues when required
- Produce clear dashboards, reports, and visualisations for stakeholders
- Communicate insights, model behaviour, and recommendations to both technical and business audiences
- Collaborate closely with data engineering, AI platform, and observability teams to productionise solutions
- Contribute to best practices around data quality, governance, and responsible use of AI
Requirements
Essential Skills
- Excel, SQL, PowerBI, AWS and quicksight
- Data analysis, exploration, and feature engineering (EDA)
- Strong applied statistics and machine learning foundations
- Python-based data science and ML stack (e.g. pandas, NumPy, scikit-learn, PyTorch / TensorFlow)
- Data engineering skills: ETL design, batch and streaming data processing
- Experience with distributed data systems (e.g. Kafka, Spark or equivalent)
- SQL and structured / semi-structured data querying
- Experiment design, model evaluation, and validation techniques
- Dashboarding, reporting, and data visualisation
- Business problem translation and requirements understanding
- Version control and collaborative development (Git)
Advantageous Skills
- MLOps practices (model packaging, deployment pipelines, monitoring awareness)
- Data governance principles (data quality, lineage, ownership, compliance awareness)
- Model evaluation, performance tracking, and drift detection concepts
- Cloud-based data and ML environments (Azure / AWS)
- Generative AI and LLM-based solution experience
- AI agent or advanced prompting familiarity
- Experience collaborating with observability and platform engineering teams
- Domain-specific knowledge aligned to business use cases
Vacancy posted 2 days ago
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