Data Scientist
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Key skills for this role
About the Role
Data Analysis & Insight Generation Analyze large datasets to identify trends and generate actionable insights for decision making and operational efficiency. Communicate finding.
Key Skills for This Role
Responsibilities
- Analyze large datasets to identify trends and generate actionable insights
- Develop and deploy machine learning models for forecasting, optimization, and risk analysis
- Prepare data through extraction, cleaning, preprocessing, and feature engineering
- Deploy models into production and monitor performance for drift or degradation
- Work with business teams to translate requirements into analytical solutions
- Ensure all AI and machine learning activities comply with governance, privacy, and regulatory requirements
Requirements
- Analyze large datasets to identify trends and generate actionable insights
- Develop and deploy machine learning models for forecasting, optimization, and risk analysis
- Prepare data through extraction, cleaning, preprocessing, and feature engineering
- Deploy models into production and monitor performance for drift or degradation
- Work with business teams to translate requirements into analytical solutions
- Ensure all AI and machine learning activities comply with governance, privacy, and regulatory requirements
Full Job Posting
Data Analysis & Insight Generation
- Analyze large datasets to identify trends and generate actionable insights for decision making and operational efficiency.
- Communicate findings through visualizations and clear storytelling.
Machine Learning & Model Development
- Develop and deploy machine learning models for use cases such as forecasting, optimization, and risk analysis.
- Apply statistical and machine learning techniques to solve complex business problems.
Data Preparation & Feature Engineering
- Prepare data through extraction, cleaning, preprocessing, and feature engineering.
- Ensure data quality and integrity for reliable model performance.
Model Deployment & Monitoring
- Deploy models into production and monitor performance for drift or degradation.
- Continuously improve models based on feedback and new data.
Collaboration & Stakeholder Engagement
- Work with business teams to translate requirements into analytical solutions.
- Collaborate with Data Engineering and Data Governance teams for end to end delivery.
AI Governance
- Ensure all AI and machine learning activities comply with governance, privacy, and regulatory requirements by following defined lifecycle processes, risk classification, and using approved governed data.
- Implement responsible and secure AI practices, including bias and fairness checks, explainability, model documentation, auditability, and collaboration with Cybersecurity and Data Governance teams.
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