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Salary
≈ $13k – $31k per year (Estimated)
Location
In office (Bengaluru)
Experience
2+ years exp
Employment
Full-Time

First seen by Alion on Oct 26, 2026.

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Onderzoeksbureau MoneyView vergaart en analyseert sinds 1993 informatie van en over financiële producten en diensten.

Job: Data Scientist

Experience: 2-6 Years

Location: Bangalore

Commitment: Full-Time

Team: Data Science

What we are looking for:

Data Scientist preferably from financial services, large banks/MNCs.

• Own end to end business problems and metrics, build and implement ML solutions

• Design, experiment and evaluate innovative models for predictive learning

• Establish scalable, efficient, and automated process for large scale data analysis, feature creation, model development and deployment

•Exposure/Experience in developing Machine Learning models using various algorithms (logistic/linear, Random Forest. Xgboost ,etc)

• Strong background in business analysis (consumer/business strategy, financial products, pricing, etc.) with very strong data analysis (Sql, excel, etc,) experience

• Strong understanding of how to structure analysis and to solve real world business problems.

• Ability to identify key drivers of business and create KPIs/modeling solutions for the same,

• Expertise in end-to-end model development and model lifecycle management (develop, deploy, monitor) is preferred

• Hands on experience in R or Python is must

• Good business understanding of fintech/personal lending space is preferred

Responsibilities:

You'll work closely with the Product and Risk Team to:

  • Define, design and deliver solutions using data science/analytics in fast paced environment
  • Evaluate and apply machine learning algorithms to build variety of data science models particularly in credit risk/unsecured lending domain but not limited to
  • Complete ownership including but not limited to identifying model development approach, building ML models, evaluation, cost benefit analysis, exploration of new data sources, implementation and monitoring of developed models.
  • Working closely with engineering team for deployment of models and infrastructure development.

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