Data Scientist

Overview

In HSBC, you will help drive data-driven decision making within the Financial Crime CDAO by designing and evolving data assets and analytics to support crime detection models. You collaborate with analysts, engineers and stakeholders across a global platform, aligning data products with regulatory and security requirements. The role combines data engineering, analytics and product thinking to improve insight, model performance and governance across data lakes and cloud environments. You will contribute to shaping the analytics roadmap and deliver impact at scale in a leading financial services organisation.

Responsibilities

• Apply SQL and Python to analyze diverse datasets and derive actionable insights for data assets and product features
• Ensure traceability of requirements and solution designs across data projects
• Analyze data-driven product functionality and advise on analyst learning and progression
• Promote adoption of data analytics practices across the analyst community
• Collaborate with stakeholders, engineers and senior team members to define problems, questions and requirements
• Assess change impact, dependencies, feasibility, scope and outputs
• Provide domain expertise to support design development, reviewing technical documents and working with data specialists
• Prepare for Design Authorities and coordinate with the development team to address challenges
• Track delivery progress against requirements and report on performance
• Work with Product Owner to manage roadmaps, epics, user stories and backlog
• Define and track metrics and KPIs for the product
• Drive Agile team performance and outcomes, leveraging domain expertise in anti-financial crime and data science

Key requirements

• Experience analyzing large, complex datasets to derive technical and business insights
• Experience with Hadoop and/or Cloud technologies (ideally GCP)
• Fluency in SQL for data analysis with advanced queries
• Proficiency in Python or other scripting languages for advanced analytics
• Familiarity with financial services and typical customer products
• Knowledge of data security, privacy and access considerations for sensitive data
• Experience in a financial crime domain is desirable
• Ability to work with moderate guidance to deliver priorities
• Strong communication of priorities and requirements to other teams
• Mentoring to junior analysts and ability to guide the team

• strong communication
• collaboration
• mentoring
• SQL
• Python
• Hadoop

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