The Role
Translate business problems into AI-enabled solutions by performing EDA, building data pipelines, developing and validating machine learning models, supporting operational data workflows, producing dashboards and reports, and collaborating with engineering and platform teams to productionize solutions while upholding data governance and responsible AI practices.
Summary Generated by Built In
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
Skills Required
- Excel
- SQL
- Power BI
- AWS
- QuickSight
- Data analysis, exploration, and feature engineering (EDA)
- Applied statistics and machine learning foundations
- Python
- pandas
- NumPy
- scikit-learn
- PyTorch or TensorFlow
- Data engineering: ETL design, batch and streaming data processing
- Distributed data systems (e.g., Kafka, Spark)
- Experiment design, model evaluation, and validation techniques
- Dashboarding, reporting, and data visualization
- Business problem translation and requirements understanding
- Version control and collaborative development (Git)
- MLOps practices (model packaging, deployment pipelines, monitoring)
- Data governance principles (quality, lineage, ownership, compliance)
- Model performance tracking and drift detection
- 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
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The Company
What We Do
Sabenza IT is a niche recruitment company specializing in Information Technology, SAP, Finance, and Engineering roles, with over 23 years of experience.
