Data Analyst

Business Objectives Recommendations

• Collaborate with various teams to collect business data to complete timely analysis/Reporting.
• Take ownership of data extraction, processing, cleansing, and verifying the integrity of data used for analysis Design, develop, and deploy analytical solutions, build data-based insights (qualitative and quantitative) to measure the efficiency and effectiveness of business and data processes.
• Explore and stay current on industry best practices, bringing insights and ideas to help drive and shape future strategy and business planning Identify key industry trends and how they impact the business / analytics & data processes.

• Hands-on experience of Python programming (such as different objects, class & instance variables, multiple inheritance, generator etc) and multiple packages (such as SciPy, NumPy, Matplotlib, Pandas, seaborn etc) is mandatory, and any packages related to statistical/Al-ML (such as Tensorflow, Keras etc] is good to have.
• Hands-on experience of advance level of Power BI (such as interactive UI/UX Features, Data integration, Customizable dashboards etc) is mandatory
• Should be self-driven, highly motivated and possess excellent multitasking skills.
• Should be passionate about solving business problems with use of data, algorithms, analytics and technology.
• Any experience related to statistical/machine learing model development is good to have but not essential.
• Any experience in credit risk and retail lending is good to have but not essential

• 2-4 years of industry experience in data technology space as an individual or team contributor.
• Strong in data structures and algorithms
• Programming experience in Python
• Advanced SQL knowledge and experience working with relational databases, query authoring (SQL)
• Familiar with data model development is preferred.
• Experience in credit risk analytics, retail lending or any of one financial service is preferred