AVP – Data and Analytics

Job Description

AVP – Data and Analytics | HSBC

The Tone:
This is a career opportunity at HSBC, located in a region where immediate local work rights are prioritized. HSBC is a leading global banking and financial services organization operating across 64 countries, focused on fostering growth for businesses and economies worldwide. This role is crucial for making a significant impression by transforming vast datasets into strategic insights that drive customer engagement and business success. Join a team where your contributions are valued in helping people achieve their financial aspirations.

The TL;DR
• Role: Mid-Career
• Type: Full-time
• Location: In-person, local region (specific location not provided)

• Mission: To leverage advanced data analytics to enhance customer engagement, drive product penetration, and deliver measurable business impact.
• Tech Stack: GCP, Hadoop, Python, SQL, Looker, GitHub

What You’ll Actually Do
• Data Transformation: Explore, cleanse, and transform extensive customer, product, channel, and interaction data across platforms like GCP and Hadoop.
• Model Development: Develop cross-sell and Next-Best-Action analytics, including propensity/uplift models, customer segmentation, eligibility rules, and prioritization logic.
• Prototype and Dashboarding: Build and iterate analytical prototypes using Python/SQL, creating decision-ready dashboards and monitoring views within Looker.
• Stakeholder Collaboration: Partner with CRM, product, and business stakeholders to define analytical use cases, establish success metrics, and design test-and-learn approaches such as A/B testing.
• Insight Translation: Translate complex data insights and modelling outcomes into actionable recommendations and implementation-ready artifacts like scoring outputs, business rules, and targeting lists.

The Must-Haves
• Background: 6+ years’ experience in banking analytics/data science, demonstrating a structured approach to delivery with deep understanding of CMB products, operating models, CRM, and customer engagement processes.
• Experience: Proven end-to-end delivery experience (development through implementation) in at least one of the following: recommendation/next-best-action, customer propensity modelling, uplift modelling, NLP/NLU, social network analysis, or path analysis. Demonstrated 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); immediate right to work locally and no relocation need will be prioritised.