Data Scientist - Bengaluru, India - Credit Saison

Credit Saison
Credit Saison
Verified Company
Bengaluru, India

1 month ago

Deepika Kaur

Posted by:

Deepika Kaur

beBee Recuiter
Description

About Credit Saison:


  • Neo-Lending Conglomerate here to enable India's credit growth story, Credit Saison India, emboldened by our Global MNC parent, is here to accelerate India's credit growth story: by building a Technology-Led Neo-Lending Conglomerate. Across our verticals, we offer bespoke solutions to meet the various
credit needs of Individuals, SMEs, FinTechs, and NBFCs.

Credit Saison India ("CS India"), having been founded in 2018, operates under the registered name Kisetsu Saison Finance India Private Limited as an MNC subsidiary of its parent company - Credit SaisonCo.

Ltd in Japan.

Across our various business verticals like Wholesale Financing, Co-origination Financing, Consumer Financing, and SME Financing we look towards reaching resilient Assets Under Management ("AUM") of US1bn in record time.

More about us on


Basic Qualifications

  • Masters or Bachelors degree in, Statistics, Economics, Machine Learning, Operations
  • Research, Computer Science or other quantitative fields. (If M.S. degree, a minimum of
  • 1+ years of industry experience required and if Bachelor's degree, a minimum of 2+ years
- of industry experience required)

  • Proficiency in SQL and other analytical tools/scripting languages such as Python or R
  • Deep understanding of statistical concepts including descriptive analysis, experimental
- design and measurement, Bayesian statistics, confidence intervals, Probability
- distributions

  • Should have an understanding of defining and Testing of Hypothesis, statistical measure
- of central tendency, Population and sample, sampling Techniques, Correlation and its
- measures and CL theorem

  • Proficiency with statistical and data mining techniques including generalized linear
- model/regression, logistic regression, random forest, boosting, trees,dimensionality
- reduction algorithms

  • Proficiency with machine learning techniques such as clustering, decision tree learning,
- naive Bayes

  • Able to deal well with uncertainty and unstructured problems to be solved
  • Should have an experience working with structured and unstructured data with applied
  • Data science/Machine learning techniques
  • Define experiments based on the model to understand and thus enhance the model
  • Experience in retail lending is a plus

Key Responsibilities
- collections scorecard using techniques such as linear model/regression, logistic
- regression, random forest, boosting/bagging trees, dimensionality reduction algorithms

  • Optimize models' outcomes to help business and drive growth
  • Analyze, interpret and present outcome/results to stakeholders; Set up model monitoring
- and understand the reasons of model expectations vs actual outcome

  • Own and deliver multiple and complex analytic projects. This would require an
- understanding of business context, conversion of business problems in modeling, and
- implementing such solutions to create business value.
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