We are looking for a Data Scientist to join a growing team within a global technology organisation. This role focuses on using data science and quality management techniques to improve the accuracy and integrity of large-scale search and machine learning recommendation systems impacting millions of users world-wide.
The ideal candidate is passionate about data quality, risk assessment, and automation, and enjoys building tools that make processes smarter and more efficient.
Key Responsibilities
- Design and implement data quality metrics, sampling methods, and audit frameworks.
- Conduct statistical analysis to identify anomalies and ensure rating accuracy.
- Build automation tools and self-serve dashboards to streamline quality checks.
- Collaborate closely with global operations and data engineering teams.
- Develop Python-based solutions to process, evaluate, and improve data reliability.
Requirements
- Strong analytical and statistical skills, with experience in data quality management or data science.
- Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL for data querying and analysis.
- Experience with data visualization (Tableau, Power BI, or similar).
- Knowledge of quality assurance principles and risk identification.
- Excellent communication skills and a strong sense of ownership.
- Experience developing self-serve tools or web applications using Python frameworks (e.g. Flask, Streamlit, Spark) is preferred.
- Exposure to advanced statistical models (Bayesian analysis, survival analysis, etc.) and advanced machine learning algorithms (e.g., decision trees, clustering, time-series forecasting) is an advantage.
What You’ll Gain
- Opportunity to contribute to the quality and accuracy of products used by millions of users worldwide.
- Join a fast-moving, high-impact team working across data science, quality operations, and automation engineering.
- Work with cross-functional partners across data, search, and content domains.
We regret to inform that only shortlisted candidates will be notified.