Data scientist / ML Engineer - US Client (Analytics)

Aspyra Hr Services; Gurugram District, Bengaluru, Pune District; Hybrid; INR 30,00,000 - 45,00,000; Full time

Job summary

A professional services firm in India seeks a seasoned expert in Python and Machine Learning for a banking model development role. The ideal candidate will have over 7 years of experience in designing and implementing credit risk models, along with the ability to analyze large datasets and collaborate effectively with product managers. Immediate joining is preferred, and a strong knowledge of IFRS 9 is required.

Qualifications

• 7+ years experience in Python and Machine Learning.
• 3+ years experience in predictive modeling.
• Experience with unstructured data (text) and IFRS 9 models.

Responsibilities

• Design, build, and implement credit risk models.
• Analyze large datasets to identify trends and risk factors.
• Collaborate with product managers and stakeholders for software solutions.

Skills

Python

Machine Learning

Data Analysis

Statistical Analysis

R Programming

Job description

Salary : 30 to 45 LPA

Exp: 7 to 12 years

Location :Mumbai Only

Notice: Immediate to 30 days..!!

Roles & responsibilities:

7+ 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.