Senior Quantitative Modeler

We are looking for an experienced
Senior Quantitative Modeler
to join a high-impact initiative led by a Central Bank in Uzbekistan.

The goal of the project is to develop a
credit scoring model
that predicts the
probability of default (PD)
for micro, small, and medium-sized enterprises (MSMEs) using both
transactional
and
alternative data
sources (such as utility payments and fines).

This is a unique opportunity to contribute to a
national-scale financial infrastructure project
that will directly support lending decisions across the country.

Key Responsibilities

• Design, develop, and validate
  credit scoring and PD models
  in Python.
• Build and optimize
  quantitative and machine learning models
  using transactional and alternative datasets.
• Work with
  large-scale datasets (20+ TB)
  to extract insights and ensure data quality.
• Ensure
  model scalability, interpretability, and robustness
  .
• Collaborate closely with analysts, consultants, and Central Bank representatives.
• Prepare
  technical documentation and model methodology
  for delivery.

Requirements

• 8+ years of experience in
  risk modeling, quantitative finance, or credit scoring
  .
• Strong expertise in
  Python
  (Pandas, NumPy, scikit-learn, etc.) for modeling and data science.
• Proven hands-on experience with
  statistical modeling
  and
  machine learning
  on large datasets.
• Fluency in
  Russian or Uzbek
  (mandatory).
• Working proficiency in
  English
  is preferred.
• Excellent analytical and problem-solving skills, with a focus on model validation and performance.

What's Offered

• Opportunity to contribute to a
  national-level financial project
  with real-world impact.
• Involvement in the
  design of a large-scale scoring model
  for Central Bank implementation.
• Flexible collaboration terms and competitive international compensation.
• Work in a highly skilled and collaborative environment.