Job Description

Data scientist / ML Engineer — US Client (Analytics) US MNC (Analytics)

3+ years exp on Python, ML and Banking model development

Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model.
Contribute to how analytical approach is structured for specification of analysis
Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems
3+ years exp on ML/Python (predictive modelling).
Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business.
Create experiments and prototype implementations of new learning algorithms and prediction techniques
Collaborate with product managers, and stockholders to design and implement software solutions for science problems
Use machine learning best practices to ensure a high standard of quality for all of the team deliverables
Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization
Hands-on experience with IFRS 9 models and regulations.
Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity.
Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming.
Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs.
Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Role: Data Scientist
Industry Type: Analytics / KPO / Research
Department: Data Science & Analytics
Employment Type: Full Time, Permanent
Role Category: Data Science & Machine Learning
Education
UG: Any Graduate
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