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Data Scientist

1 month ago

Bengaluru, Karnataka, India Kaleidofin Private Limited Full time
About Kaleidofin Private Limited

Kaleidofin Private Limited is a fintech company dedicated to unlocking access to tailored finance for women, agriculture and nano entrepreneurs. We provide the ki credit platform, which combines credit health assessment (ki score), middleware rails and best-in-class risk management (ki view) to enable the financial ecosystem to better serve customers.

Estimated Salary: ₹20-30 lakhs per annum

This position is based in Chennai/Bangalore and offers a hybrid work-from-office setup.

Job Description:
  • Lead and mentor a team of data scientists/analysts to drive business growth through data-driven insights.
  • Provide analytical insights by analyzing various types of data, including mining customer data, reviewing relevant cases/samples, and incorporating feedback from others.
  • Work closely with business partners and stakeholders to determine how to design analysis, testing, and measurement approaches that will significantly improve our ability to understand and address emerging business issues.
  • Produce intelligent, scalable, and automated solutions by leveraging Data Science skills.
  • Collaborate with Technology teams on development of new capabilities to define requirements and priorities based on data analysis and business knowledge.
Requirements:
  • 5+ years in advanced analytics, statistical modeling, and machine learning.
  • Strong understanding of credit risk, full lifecycle from origination to debt collection.
  • Well-versed with ML algos, BIG data concepts, and cloud implementations.
  • High proficiency in Python and SQL/NoSQL.
  • Collections and Digital Channels experience a plus.
  • Strong organizational skills and excellent follow-through.
  • Ongoing written, verbal, and interpersonal communication skills.
Preferred Qualifications:
  • Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
  • Experience in risk and credit score domains preferred.