AVP - Machine Learning - BFS

The candidate will be expected to:

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

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

- 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 adhere to change control and testing processes for modifications to analytical models.

- 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.

Qualifications:

- The candidate should have at least 6+ years of relevant experience in analysis in retail, direct marketing, or other consumer-oriented business with large customer databases and minimum of 3+ years of experience in Operations Analytics

- Bachelor's degree in a quantitative discipline; Math, Finance, Statistics, Economics, data analytics or equivalent work/training is required; advanced degree is preferred.

- 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.

- Hands-on experience on 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

- Experience of visualization tools like Tableau is good to have.