Manager – Data and Analytics

Job Description

Manager – Data and Analytics | HSBC

The Tone:
This is an in-person, full-time role at HSBC, located locally where operations are. HSBC is one of the world’s largest banking and financial services organizations, operating across 64 countries and territories. This position is vital for leveraging data and analytics to enable businesses to thrive, economies to prosper, and ultimately help people realize their ambitions. Joining this team offers a significant opportunity to make a real impression through data-driven insights and strategic impact.

The TL;DR
• Role: Experienced Professional
• Type: Full-time
• Location: In-person, local

• Mission: To drive data-driven insights and analytical solutions that enhance customer engagement and business performance across HSBC’s operations.
• Tech Stack: GCP, Hadoop, Python, SQL, Looker, GitHub

What You’ll Actually Do
• Transform Data: Explore, cleanse, and transform large volumes of customer, product, channel, and interaction data across platforms including GCP and Hadoop.
• Develop Analytics Models: Develop cross-sell/next-best-action analytics, including propensity/uplift models, segmentation, eligibility rules, and prioritization logic.
• Engineer Features and Prototypes: Engineer features from CRM and behavioral signals, then build and iterate prototypes using Python/SQL, creating decision-ready dashboards and monitoring views in Looker.
• Partner and Communicate: Partner with CRM, product, and Business stakeholders to define use cases and test-and-learn approaches, while clearly communicating modelling approaches, assumptions, limitations, and outcomes to diverse audiences.
• Translate Insights and Drive Improvement: Translate insights into actionable recommendations and implementation-ready artefacts, driving continuous improvement through automation and modern tooling, and maintaining strong engineering discipline.

The Must-Haves
• Background: Manager career level, with a structured approach to delivery in banking analytics/data science. Strong understanding of Commercial Banking (CMB) products and operating model, particularly in CRM and customer engagement processes.
• Experience: 3+ years’ experience in banking analytics/data science, with demonstrated end-to-end delivery experience (development through implementation) in recommendation/next-best-action, customer propensity modelling, uplift modelling, NLP/NLU, social network analysis, or path analysis. Proven track record of converting data into insights and delivering measurable business impact.
• Skills: Advanced Python and SQL skills for large dataset analysis and complex statistical analysis. Strong working knowledge of GCP services and analytics tooling, coupled with a solid understanding of Hadoop concepts and ecosystem. Strong stakeholder management, presentation, and communication skills.
• Bonus: Active GitHub contributor or equivalent evidence of strong version control and collaborative coding practices. Excellent written and spoken communication skills in English.