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AVP Data scientist / ML Engineer -- US Client (Analytics)

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Hybrid

AVP Data scientist / ML Engineer -- US Client (Analytics)

Aspyra Hr Services

AVP Data scientist / ML Engineer -- US Client (Analytics)

Skills

PythonRData AnalysisMachine Learning

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹4,000,000 – ₹5,500,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

17 August 2026

What they need


Salary : 40 to 55 LPA

Exp: 8 to 12 years

Location :Gurugram /Bangalore

Notice: Immediate to 30 days..!!

Roles & responsibilities:

7+ years exp on Python, ML and 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
  • 8+ 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.

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