Senior Data Scientist
Blue Pearl HQ
Our client is seeking a Senior Data Scientist to lead the development of advanced analytics, machine learning models, and data-driven solutions that support strategic business decision-making. The successful candidate will work closely with business stakeholders, engineering teams, and leadership to extract meaningful insights from complex datasets.
Requirements
Key Responsibilities
- Design and implement advanced predictive models.
- Develop machine learning and statistical solutions.
- Analyse large and complex datasets.
- Build forecasting, classification, and recommendation models.
- Drive data-driven decision-making across business functions.
- Present insights and recommendations to stakeholders.
- Mentor junior Data Scientists and Analysts.
- Collaborate with Data Engineering teams to build scalable data solutions.
- Deploy and monitor machine learning models in production.
Minimum Requirements
- Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related field.
- Master's Degree preferred.
- 5+ years of Data Science experience.
- Proven experience delivering machine learning solutions in production environments.
Technical Skills
Essential
- Python
- SQL
- Machine Learning
- Statistics
- Predictive Analytics
- Data Modelling
- Data Visualisation
- Feature Engineering
Tools & Technologies
- Python
- Pandas
- NumPy
- Scikit-Learn
- TensorFlow or PyTorch
- SQL Server
- PostgreSQL
- Power BI
- Tableau
- Jupyter Notebooks
Cloud Platforms
- AWS
- Azure
- Google Cloud Platform
Preferred Experience
- Generative AI
- Natural Language Processing (NLP)
- MLOps
- Data Engineering exposure
- Big Data technologies
- Spark
- Databricks
Key Competencies
- Advanced Analytical Skills
- Business Acumen
- Problem Solving
- Communication Skills
- Leadership & Mentoring
- Stakeholder Management
Preferred Certifications
- AWS Certified Machine Learning
- Microsoft Azure Data Scientist Associate
- Google Professional Machine Learning Engineer
- Databricks Certifications
Success Measures
- Delivery of business value through analytics.
- Accuracy and performance of predictive models.
- Stakeholder satisfaction.
- Successful deployment of production-ready solutions.
- Continuous improvement of data-driven capabilities.
