Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.
As a member of the Corporate and Investment Banking Marketing Analytics and Insights team, you will play a pivotal role in developing innovative, AI-powered solutions that promote business growth and career advancement. In this role, you will be the analytical backbone behind our marketing commercialization efforts — transforming complex, multi-source data into clear, actionable insights that directly influence revenue strategy and campaign effectiveness. You will work hands-on with large-scale datasets, build robust analytical frameworks, design dashboards, and deliver insights that help marketers optimize targeting, measure ROI, and identify the next best strategy for engaging clients. This is not a passive reporting role — you will be expected to think critically, challenge assumptions, and proactively surface opportunities hidden in the data. You’ll collaborate with a dynamic and forward-thinking team focused on measuring and amplifying the impact of global marketing initiatives. In this foundational position, you will lead the technical execution of data engineering and analytics projects—building intelligent data tools, uncovering actionable insights, and spearheading revenue optimization through advanced data science and machine learning methodologies.
Job Responsibilities
- Develop and deliver analytics that directly support revenue generation, including client propensity modeling, opportunity sizing, and next-best-action frameworks. Translate analytical findings into clear strategic recommendations for business and marketing stakeholders.
- Measure and evaluate the effectiveness of marketing campaigns and programs across channels. Build frameworks for attribution, engagement scoring, and audience segmentation that enable marketers to target clients with greater precision and impact.
- Design, build, and maintain interactive dashboards and reporting solutions that provide stakeholders with self-service access to key marketing and revenue metrics. Ensure reporting is accurate, timely, and aligned with business priorities.
- Collaborate with marketing, sales, and business teams globally to understand their analytical needs, translate business questions into data problems, and deliver insights that drive action. Communicate complex findings in a clear, compelling manner to both technical and non-technical audiences.
Required Qualifications, Capabilities, and Skills
- Minimum 4 years of hands-on experience in data analytics or a related quantitative role.
- Advanced proficiency in SQL — you should be highly comfortable writing complex queries, optimizing performance, and working across large relational databases.
- Strong proficiency in Python for data manipulation, analysis, and automation (e.g., pandas, NumPy, and related libraries).
- Proven ability to create dashboards and visualizations using tools such as Tableau, Power BI, or equivalent platforms.
- Strong analytical thinking — demonstrated ability to take ambiguous business questions, structure them as data problems, and deliver clear, insight-driven answers.
- Excellent communication skills — you can present data findings and recommendations to senior stakeholders and non-technical audiences with clarity and confidence.
- Bachelor's degree in quantitative or technical field such as Computer Science, Data Science, Statistics, Information Systems, Economics, or equivalent practical experience.
Preferred Qualifications, Capabilities, and Skills
- Familiarity with machine learning concepts and experience building basic predictive models.
- Conceptual understanding of Generative AI — while hands-on experience is not required, a solid grasp of Gen AI concepts such as large language models, prompt engineering, retrieval-augmented generation, and how these technologies can be applied to enhance analytics and marketing workflows would be highly valued.
- Data engineering experience — familiarity with building and maintaining ETL/data pipelines, extracting, transforming, and loading data from disparate sources into structured, analysis-ready formats.
- Experience working with marketing data platforms such as Marketo, Adobe Analytics, Salesforce, or Google Analytics.
- Experience with cloud-based data platforms such as Databricks, Snowflake, or AWS-based analytics services.
- Exposure to AI-driven BI tools such as ThoughtSpot, Databricks Genie, or similar next-generation analytics platforms.
- Experience in financial services, banking, or B2B marketing analytics environments.