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