Join our Commercial & Investment Bank Marketing Analytics & Insights team as a Marketing Data & Analytics Associate and help turn data into decisions that matter. You’ll work alongside marketers and business leaders to translate complex, multi-source information into clear, actionable insights that shape strategy and elevate how we engage clients—delivering the right message to the right audience at the right time. This role goes beyond reporting: you’ll build analytical frameworks, develop dashboards, and surface growth opportunities using SQL, Python, and advanced techniques including machine learning and Generative AI. If you’re energized by solving meaningful problems, challenging assumptions, and communicating insights with impact, this is your opportunity to drive measurable results.

As a Marketing Data & Analytics Associate within our Commercial & Investment Bank Marketing Analytics & Insights team, you sit at the intersection of data, strategy, and marketing impact. You'll partner closely with marketers and business stakeholders to transform complex, multi-source data into clear, actionable insights — the kind that directly shape strategy and help us reach the right clients with the right message at the right time. This isn't reporting for reporting's sake: you'll build analytical frameworks, design dashboards, and uncover the opportunities hidden in the data, using SQL, Python, and the power of machine learning and Generative AI. You'll think critically, challenge assumptions, and communicate your findings with clarity to both technical and non-technical audiences. If you're ready to see your work move the needle on real business outcomes, we'd love to have you join us.

Job Responsibilities:

• Revenue & Strategy Analytics: Develop and deliver data solutions and analytics that directly support revenue generation, including client propensity modeling, opportunity sizing, and next-best-action frameworks. Translate findings into clear strategic recommendations for stakeholders.
• Campaign & Marketing Insights: Measure and evaluate the effectiveness of marketing campaigns across channels. Build frameworks for attribution, engagement scoring, and audience segmentation that enable precise, high-impact client targeting.
• Dashboards & Visualization: Design, build, and maintain interactive dashboards and reporting solutions that give stakeholders self-service access to key marketing and revenue metrics — ensuring reporting is accurate, timely, and aligned with business priorities.
• Stakeholder Partnership: Collaborate with marketing, technology, and business teams globally to understand their analytical needs, translate business questions into data problems, and communicate complex findings clearly to both technical and non-technical audiences.
• Entrepreneurial Delivery: Drive results with an entrepreneurial mindset in a fast-paced, high-impact environment.

Required qualifications, capabilities, and skills:

• 1+ years of hands-on experience in data analytics or a related quantitative role.
• Advanced proficiency in SQL — 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).
• Conceptual understanding of Generative AI — while hands-on experience is not required, a solid grasp of concepts such as large language models, prompt engineering, and retrieval-augmented generation, and how these can enhance analytics and marketing workflows
• Proven ability to create dashboards and visualizations using tools such as Tableau, Power BI, or equivalent platforms.
• Familiarity with machine learning concepts and experience building basic predictive models.
• Strong analytical thinking — able to take ambiguous business questions, structure them as data problems, and deliver clear, insight-driven answers.
• Excellent communication skills — able to present findings and recommendations to senior stakeholders with clarity and confidence.
• Bachelor's degree in a quantitative or technical field such as Computer Science, Data Science, Statistics, Information Systems, or equivalent practical experience.

Preferred qualifications, capabilities, and skills:

• Data engineering experience — familiarity with building and maintaining ETL/data pipelines and transforming 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.
• Graduate degree in a technical or quantitative discipline.
• Experience in financial services, banking, or B2B marketing analytics environments.