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# Associate, Client Intelligence (Data Scientist)

- **Company:** HSBC
- **Location:** New York, NY, United States
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Information Engineering, Data Visualization, Apache Hadoop, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Power BI, SQL Databases, Tableau (Software), Cloud Platform System, Feature Engineering, Apache Spark, Information Technology, Performance Monitor
- **Published:** August 31, 2026
- **Apply:** https://www.manhattanjobs.com/job.asp?id=3370736532&tx=ZT2322THT&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's degree required; Master's preferred in a quantitative field (Data Science, Statistics, Computer Science, Mathematics, Economics, or similar).
 * Strong experience in analytics/data science, ideally within financial services or a commercial analytics environment.
 * Working knowledge of Python (preferred), SQL; experience with modelling techniques (predictive, statistical, ML). Familiarity with big data and/or cloud environments (e.g., Spark/Hadoop; AWS/Azure/GCP) and visualization tools (Power BI/Tableau).
 * Experience with disciplined coding practices and have a systems mindset
 * Familiarity with AI-assisted analytics and a practical approach to when to use it and how to validate outputs.
 * Working knowledge of CIB client segments and commercial drivers; experience in at least some of: client segmentation, wallet sizing, client profiling, peer benchmarking, pipeline/sales analytics.
 * Curious, structured problem-solver; able to spot patterns, test hypotheses, and communicate findings clearly
 * Able to explain methods and results to non-technical audiences; comfortable presenting insights to stakeholders and iterating based on feedback.
 * Comfortable operating in a global matrix; organized, delivery-focused, and able to manage multiple priorities.

## Description

Our purpose - Opening up a world of opportunity - explains why we exist. Here at HSBC, we use our unique expertise, capabilities, breadth, and perspectives to open up new kinds of opportunity for our more than 40 million customers. We're bringing together the people, ideas and capital that nurture progress and growth, helping to create a better world - for our customers, our people, our investors, our communities, and the planet we all share.

In compliance with applicable laws, HSBC is committed to employing only those who are authorized to work in the US. Applicants must be legally authorized to work in the U.S. as HSBC will not engage in immigration sponsorship for this position.

CBA (Client & Banking Analytics) transforms data into strategic analytics that improve commercial performance across HSBC CIB (Corporate and Institutional Banking). We support better decisions on where to invest time and resources across clients, products, and channels, using consistent methodology and strong governance.

As an Associate in Client Intelligence, you'll help deliver advanced analytics that commercialize HSBC's internal client data and integrate external datasets to generate actionable insights. You'll own defined analytics workstreams end-to-end (from problem framing to delivery), partnering closely with stakeholders to identify growth opportunities, define high-potential clients, and optimize customer value to guide investment decisions across clients, products, and channels. Where appropriate, you'll use approved AI tools, including emerging agentic workflows and AI-driven analytics, to accelerate delivery, with appropriate validation and governance.

We are looking for individuals who are not only analytically strong, but also curious about how emerging AI capabilities can enhance analytical workflows, productivity, and insights generation.

As our Associate, Client Intelligence you will:

 * Analytics Delivery: Extract, clean, and join datasets (internal and external) using SQL and Python/R; perform exploratory analysis and basic feature engineering; build, test, and deploy analytical models for client profiling, segmentation, wallet sizing, customer value measurement, and growth use cases. Use approved AI tools, including agentic workflows, to support analysis and automation where relevant.
 * Insight Generation & Storytelling: Translate analysis into clear recommendations, commercial implications, and practical next steps for frontline and CIB leadership.
 * Stakeholder Partnership: Work with coverage, product, and servicing teams to understand needs, refine requirements, and support adoption of analytics outputs into business routines.
 * Data & Quality Management: Partner with data engineering/technology to access data, improve data quality, document assumptions, and follow governance standards.
 * Operational Excellence: Maintain robust model documentation, performance monitoring, and repeatable processes; contribute to reusable code and standard methodologies.
 * Collaboration & Coaching: Support junior colleagues through peer review, knowledge sharing, and best-practice guidance (without necessarily being a formal people manager).


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