Marketing Analytics Analyst – Python, SQL and Machine Learning

Role Overview

The TTS Analytics team provides analytical insights to the Product, Pricing, Client Experience and Sales functions within the global Treasury & Trade Services business. The team works on business problems focused on driving acquisitions, cross-sell, revenue growth & improvements in client experience.

What You Will Do

The role will involve working on multiple analyses through the year on business problems across the client life cycle – acquisition, engagement, client experience and retention – for the TTS business, leveraging multiple analytical approaches, tools and techniques, working on multiple data sources to provide data driven insights to business and functional stakeholders.

Why It Might Be a Fit

The ideal candidate will have experience in marketing analytics, experience with business problems around sales/marketing strategy optimization, pricing optimization, client experience, cross-sell and retention, and experience with predictive modeling using Machine Learning.

Requirements

• Bachelor’s Degree with 5-8 years of experience in data analytics, or Master’s Degree with 4-8 years of experience in data analytics, or PhD.
• Marketing analytics experience
• Experience on business problems around sales/marketing strategy optimization, pricing optimization, client experience, cross-sell and retention
• Experience across different analytical methods like hypothesis testing, segmentation, time series forecasting, test vs. control comparison etc.
• Predictive modeling using Machine Learning
• Experience with unstructured data analysis, e.g. call transcripts, using Natural language Processing (NLP)/ Text Mining
• Strong logical reasoning and problem solving ability
• Proficient in converting business problems into analytical tasks, and analytical findings into business insights
• Proficient in formulating analytical methodology, identifying trends and patterns with data
• Has the ability to work hands-on to retrieve and manipulate data from big data environments
• Proficient in Python/R, SQL
• Experience in Hive
• Proficient in MS Excel, PowerPoint
• Good to have: Experience with PySpark, Experience with Tableau

Tagged as: Python, SQL