Senior Data Analyst
4 days ago
Responsibilities will include -:
1. Functional Expertise
• Create, Update and manage data warehouse on daily basis.
• Strong eye for business and demonstrated ability to create and drive strategic insights roadmaps to deliver against core business needs. Ability to plan and stage the insights work to be done and drive the execution of this leveraging other Insights individuals.
• Conduct analytics on loan portfolio, including trend analysis around growth, with various cuts (by product, partner, etc.)
• Conduct analytics on risk performance of loan portfolio, including conducting different NPA cuts
• Create basic live dashboards covering metrics & trend analysis (incl. visual representations/ charts) of business performance, risk performance, etc.
2. Problem Solving
• Excellent technical competence and experience performing analysis across a breadth of techniques (e.g. exploratory analytics / causal inference / experimentation / ML techniques)
• Identify gaps in data, additional data needed to fulfill the defined objectives, and work with Business team to address those gaps.
• Create automate reports with the help of Python, Metabases and other relevant tools for offline, online data system.
3. Interaction:
• Ability to communicate effectively and influence senior leadership
• Ability to communicate technical and statistical concepts clearly and concisely among audiences of varying technical levels
• Put in place the process & right tool for enabling data functioning
To succeed in the role-:
Qualification & Experience
● B.com, M. Com, MBA, MSC-IT, MCA, B.Tech / M.Tech /Masters in Statistics, Computer
Science, Engineering or related areas
● Experience of working in Data analytics in Banking/ NBFC/ Fintech or related space
● 5 years of progressive business experience involving data and analytics. Experience in
analytics in banking and financial segment; experience in Credit risk analytics is a plus
Skills & know-how
● Strong command on SQL, Python, Advance Excel, Google spreadsheet and quantitative
programming skills
● Extensive experience working with large scale datasets and using data engineering best
practices
● Technical competency: Convert data into the various report, real time data fetching, Proper
use case and justification to the business, good hands-on Python/ R or relevant data warehouse to create and use data with various ways to insert/update and fetch correct data.
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