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About the Role

As an individual contributor in the Data Science and AI Division (DSAD), you will apply advanced analytics and machine learning to unlock data value, delivering scalable insights that inform strategy and operational efficiency. Your work will contribute to a data-driven culture, enabling smarter decision-making and impacting areas like fraud detection and policy shaping.

Responsibilities

• Collaborate with business teams to understand data needs and contribute to data science projects, developing predictive models, dashboards, and analytical products.
• Ensure data integrity and accuracy by assessing data quality, identifying anomalies, and working with data engineers to resolve issues.
• Develop models for risk scoring, fraud detection, and regulatory reporting using descriptive analytics and advanced machine learning to inform decisions.
• Translate analytical findings into clear visualizations and actionable recommendations for business teams and leadership.
• Promote data literacy and best practices to foster a culture that values data as a strategic asset.

Requirements

• Experience building machine learning models at scale, including models for risk scoring or fraud detection.
• Exposure to deploying analytical solutions on enterprise data platforms, cloud platforms (e.g., AWS), containerization tools (e.g., Kubernetes), or CI/CD pipelines.
• Self-driven with the ability to manage data science tasks independently while being open to guidance.
• Proactive and adaptable, capable of managing multiple tasks and delivering results in a fast-paced environment.
• Enjoys solving complex problems and translating business and regulatory challenges into analytical solutions.
• Thrives in collaborative environments with product managers, engineers, and business teams.
• Ability to communicate analytical findings clearly and persuasively to technical and non-technical audiences.
• Successful candidates will be offered a 2-year contract, with potential for extension or permanent tenure.
• Candidates are encouraged to sign up for a Careers & Skills Passport (CSP) account and include their CSP public profile in their resume.

Skills

• Statistical analysis
• Machine learning
• Predictive modelling
• Python
• R
• SQL
• Spark
• Tableau
• Power BI

Location

• Remote

Work Type

• Contract
• Full-time

Experience Level

• Mid-level