• Scienaptic - Principal Data Scientist - Credit Risk Analytics Jobs in Bangalore,India

  • Scienaptic Systems

Job Description:

Scienaptic (wwwscienapticcom) is a new age analytics company that offers end-to-end decisioning solutions powered by our Machine Learning (ML) and Artificial Intelligence (AI) based platform - Ether- Ether is a transparent and impactful platform for leveraging the full power of machine learning in Credit Decisioning We are creating ecosystems where artificial intelligence (AI) and human intelligence can work together to create greater consciousness for specific business use cases such as fraud, underwriting etc

We are looking for a Principal Data Scientist in Credit Risk Analytics to join our Data Science team


- Experience in Financial Services/ Fintech/ BFSI along with Credit Risk in Retail Banking and Data Science

- Minimum 7 years of experience in building predictive models (Application Score Card, Behaviour Score Card, Collection Score Card, Loan Pricing, Loss Forecasting, Cross Sell Model)

- Develop and Maintaining Credit Risk Models & Strategies

- Experienced Statistical software skills (eg SAS, R, Python)

- Strong understanding of ML libraries and applications

- Strong experience in leading credit risk model development, validation, deployment, and documentation

- Analytically oriented with ability to grasp complex risk management strategies, processes, models and draw insights / identify areas of opportunity

- Strong track record of delivering on high value / critical projects Ability to communicate with senior stakeholders crisply and confidently on findings, status, bottlenecks, and escalations

- Ability to work independently, structure analyses and handle multiple priorities

- Hold a degree from tier 1 business schools

- Proven track record of delivering in a start-up environment would be a plus

- Strong written and oral communication skills

Profile Summary:

Employment Type : Full Time
Salary : Not Mentioned
Deadline : 20th Feb 2020

Key Skills:

Company Profile:

Not Mentioned

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