Analyst | Senior Analyst - Banking & Financial Services

Work Location - Chennai, Bangalore, Hyderabad

About the role:

As a Analyst or Senior Analyst - BFS, you will work with Clients in Banking & Financial Services, & help translate business problems into unambiguous analytics problem statements and design analytical frameworks to address them. On a typical work day, you could be doing one or more of the following:

• Collaborate with the team of data scientists and engineers to plan and drive the execution of business solutions
• Contribute to client presentations, reports, QBRs etc
• Handle client discussions in structured project settings

Domain Understanding:

• Awareness of the Banking regulatory landscape
• Awareness of common AI and automation use cases in BFS (fraud detection using ML, credit scoring, robo-advisors, chatbots). Can identify basic applications of analytics in operations.
• Knowledge of the concepts in any or multiple use cases like customer segmentation, CLTV, Customer attrition and retention, next best product/cross sell and has had contributed hands on to atleast a part of any of these project if not end to end. Involvement in atleast any one of Model Validation, Model Performance Monitoring and Model Development is desired

Required Skills & Experience:

• 1-3 years of relevant experience in Analytics projects in BFS domain for any geography
• At least 1 year of experience working for global Banks or financial services in the area of either Credit, Fraud, Marketing, Operations etc.. on AI or analytics engagements
• Strong communication & experience in client communication.
• Awareness of storytelling with PPT & has effectively communicated with clients to understand their basic requirements, communicate status updates, or escalation calls
• Hands-on experience in preparing

  Powerpoint / Google Slides

  presentations & presenting them to key stakeholders
• Hands-on experience with

  Excel/ Google Sheets

  to review, sanitize, manipulate data
• Hands-on experience of querying data using

  SQL

  on traditional RDBMS databases, and/or big data environments such as Hadoop/Hive/Spark.
• Ability to analyse and visualize data one or more tools such as

  Tableau, PowerBI

• Intermediate experience in DS/ML/AI programming tool of

  Python

• Exposure to low-code no-code tools GPT, CLausde, Lovable, Gemini
• Appreciation of different types of Statistical / Machine Learning / AI techniques, when and why they are used
• Interpret results from a business viewpoint (the expectation is not a data scientist expert-level proficiency, but a clear conceptual understanding)
• Ability to leverage analytics to solve structured or unstructured problems and interpret results