Business Analyst - Retail Banking Domain

- Partner with onshore leaders to drive projects assigned to the team

- Contribute to data mining architectures, modeling standards, reporting, and data analysis methodologies

- Exhibit thought leadership and demonstrate analytical thinking to drive insights from data

- Perform in depth analysis to resolve a business problem by employing the appropriate tools available in the enterprise

- Identify new opportunities to bring new process improvements.

- Communicate data findings through engaging stories that are easy to understand

- Quickly assesses the big picture in complex situations and identify what is critical

- Routinely make decisions for best course of action and to drive business solutions

- Support internal and external processes and workflows, suggest improvements based on data analysis and provide insights into the enterprise operations

- Work with business domain experts to identify data relevant for analysis

- Provide and apply quality assurance best practices for data mining/analysis services

- Develop new analytical methods and/or tools as required.

- Adhere to change control and testing processes for modifications to analytical models

- Collaborate with unit managers, end users, development staff, and other stakeholders to integrate data mining results with existing systems

- Extract reports/ data, analyze and provide recommendations for the project undertaken

- Respond to and resolve data mining performance issues. Monitor data mining system performance and implement efficiency improvements

- The candidate should have 5+ years of relevant experience in Operations Research and Analytics

- Bachelor's degree or equivalent in Statistics, modeling or data Analytics

- Strong Retail Banking is a must

- Experience working with the US Retail market is a plus

- Experience of working with International Partners in an Offshore and Onshore model is a plus

- Demonstrated proficiency with Microsoft Office (Excel, PowerPoint)

- Proficiency in critical thinking and problem solving

- Strong verbal and written communication skills

- Strong understanding of data mining models, structures, theories, principles, and practices, including machine learning, statistics and text mining techniques

- Excellent knowledge of statistical and modeling tools such as SAS, R, Python and SQL

- Experience in large scale data handling

- Ability to guide and conduct research and drive valuable insights from data

- Strong familiarity and experience with statistics, modeling, segmentation, optimization, forecasting, demand mitigation is a must

- Should have strong understanding of Queuing theory

- Experience of visualization tools like Tableau is good to have