Role summary
Lead the end-to-end data science lifecycle from strategic problem identification to technical execution, ensuring advanced machine learning and optimization solutions drive measurable business value.
Responsibilities
- Align data science initiatives with business goals and identify high-impact use cases
- Actively design, build, and review models (ML, forecasting, optimization), perform complex analyses, and validate results
- Lead development of machine learning, forecasting, and optimization solutions
- Ensure data governance, integrity, and compliance standards
- Implement MLOps practices for deployment, monitoring, and scalability
- Translate business needs into analytical solutions and communicate insights clearly
- Prioritize projects, track KPIs, and ensure measurable business impact
- Promote experimentation, new technologies, and continuous improvement
Requirements
- Bachelor's degree in Statistics, Data Science, Computer Engineering, Science, Mathematics, Information Technology, or Artificial Intelligence
- Minimum 5 years' experience in data science
- Programming & Data: Python/R, SQL, and Azure ML
- Machine Learning: Supervised/unsupervised learning, forecasting, optimization
- Statistics, A/B testing, predictive and prescriptive modelling
- Model deployment, monitoring, CI/CD, versioning
- Solution Design: Scalable, reliable, and production-ready model architectures
- Leadership & Mentoring, Decision Making
Education
Bachelor's degree in Statistics, Data Science, Computer Engineering, Science, Mathematics, Information Technology, or Artificial Intelligence
Experience
Minimum 5 years' experience in data science
Skills
- Python/R
- SQL
- Azure ML
- Supervised learning
- Unsupervised learning
- Forecasting
- Optimization
- A/B testing
- Predictive modelling
- Prescriptive modelling
- Model deployment
- Monitoring
- CI/CD
- Versioning
- Scalable model architectures
- Leadership
- Mentoring
- Decision Making
Education · Experience · Type
Bachelor'sRequires 5+ yearsSalary not stated