Key Responsibilities

• Use automated tools to extract data from primary and secondary sources.
• Work with technical teams to implement extraction pipelines and any maintenance improvements in the data.
• Ensure data quality by maintaining and updating the data extraction pipeline as required.
• Use statistical tools to identify, analyze, and interpret patterns and trends in complex datasets to identify improvement opportunities in the product.
• Analyze local, national, and global trends that impact both the organization and the industry.
• Develop a deep understanding of the product lifecycle, customer journey, backend checks and associated data.
• Write automated scripts to check the accuracy of data shared with partners across multiple systems.
• Work with technical and product teams to identify process improvement opportunities, propose system modifications, and devise data governance strategies.
• Create reports and dashboards for internal and external stakeholders enabling them to make informed decisions about the product based on business performance and predictions. 

Knowledge, Skills & Experience

• 2+ years of Proven working experience in data analysis.
• Strong mathematical skills to help collect, measure, organize and analyze data.
• Ability to work independently and explore data to provide innovative solutions to a business problem.
• Proficiency in SQL and Python.
• Experience in ETL processes using SQL stored procedures.
• Experience in database design development, data models, techniques for data mining and segmentation.
• Understanding of Relational database architecture.
• Experience in MS Office (Excel, PowerPoint etc.), SAS.
• Knowledge of data visualization tools like Tableau, Metabase, and Qlik.
• Good communication skills to present solutions to the management. 

Good to Have:

• Knowledge about the practices and procedures in US unsecured lending industry.
• Knowledge about supervised and unsupervised model development.