Data Scientist

Kaleidofin; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Kaleidofin is seeking a lead data scientist to guide a team of analysts and data scientists in building analytical solutions that address core business issues. You will design and implement analytics, establish measurement approaches, and partner with business stakeholders to translate data-driven insights into actionable outcomes.

The role emphasizes ownership, collaboration with technology teams, and delivering scalable data science initiatives in a dynamic fintech environment in Bengaluru.

Qualifications

• 1 to 6 years in advanced analytics, statistical modelling, and machine learning.
• Best practice knowledge in credit risk - full lifecycle from origination to debt collection.
• Proficient with ML algorithms, big data concepts, and cloud deployments.
• High proficiency in Python and SQL/NoSQL.

Responsibilities

• Lead and mentor a team of data scientists/analysts.
• Provide analytical insights by analysing various data types including customer data and case reviews.
• Collaborate with business partners to design analysis, testing, and measurement strategies.
• Develop intelligent, scalable, automated solutions leveraging data science skills.
• Work with Technology teams to define requirements and priorities based on data analysis.

Skills

Python

SQL/NoSQL

Leadership

Analytics

Communication

Problem solving

Self-starter

Emotional intelligence

Data analysis

Continuous learning

Tools

Spark

Hadoop

Cloud computing

Hive

MapReduce

Pig

Job description

Responsibilities

• Lead and mentor a team of data scientists/analysts.
• Provide analytical insights by analysing various types of data, including mining our 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.
• Work closely with Technology teams on the development of new capabilities to define requirements and priorities based on data analysis and business knowledge.
• Developing expertise in specific areas by leading analytical projects independently, while setting goals, providing benefit estimations, defining workflows, and coordinating timelines in advance.
• Providing updates to leadership, peers, and other stakeholders that will simplify and clarify complex concepts and the results of analyses effectively, with emphasis on the actionable outcomes and impact on business.

Requirements

• 1 to 6 years in advanced analytics, statistical modelling, and machine learning.
• Best practice knowledge in credit risk - strong understanding of the 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 are a plus.
• Strong organisational skills and excellent follow-through.
• Outstanding written, verbal, and interpersonal communication skills.
• High emotional intelligence, a can-do mentality, and a creative approach to problem solving.
• Takes personal ownership, Self-starter - ability to drive projects with minimal guidance and focus on high-impact work.
• Learns continuously; Seeks out knowledge, ideas, and feedback.
• Look for opportunities to build one's skills, knowledge, and expertise.
• Experience with big data and cloud computing, viz. Spark, Hadoop (MapReduce, PIG, HIVE)
• Experience in risk and credit score domains preferred.