Data Scientist Lead
3 days ago
**Requisition ID**:6884
**Country**:SG
**Work Schedule**:Non-Shift Work Schedule
**Employment Type**:Permanent
**Description**:
**Key Responsibilities**:
- Collaborate with product owners, data engineers, and partners across all product development stages - from concept and design to prototyping, testing, data curation, deployment, industry scaling, and end-of-life.
- Collect, process, and analyse large data sets from various sources.
- Design, build, and validate machine learning models and statistical algorithms.
- Perform exploratory data analysis to uncover insights and trends.
- Collaborate with stakeholders to define data requirements and objectives.
- Communicate findings and recommendations to non-technical stakeholders.
**Qualifications**:
- At least 10 years of experience in a proven role as a data scientist or similar function, with at least 3 years in managing a team of data scientists, machine learning engineers and big data specialists
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
- Strong knowledge of statistical methods and machine learning techniques such as regression, classification, clustering, time series forecasting, and anomaly detection.
- Strong programming skills in Python (and/or R), with hands-on experience using machine learning libraries such as scikit-learn, XGBoost, TensorFlow, and PyTorch.
- Solid understanding of data wrangling, exploratory data analysis, feature engineering, and model evaluation, paired with the ability to select or define appropriate success metrics grounded in real business context.
- Familiarity with MLOps practices including model deployment, monitoring, and versioning of ML artifacts (e.g., MLflow, Airflow, integration with CI/CD pipelines).
- Experience using Git for version control and familiarity with common collaboration tools such as GitHub or GitLab.
- Experience with data visualization tools like Tableau or Power BI.
- Excellent problem-solving skills and attention to detail.
- Strong storytelling, communication and collaboration skills.
- Awareness of data governance, privacy, and security practices (e.g., GDPR, PDPA).
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