Quantitative Analyst

Quant Analyst AI/ML, Risk Analytics & Payment Processing"

Job Title:

Job Location:

Experience Required:

Job Requirement:

• Develop and maintain Financial Crime and AML Models

   aligned to regulatory frameworks and organizational model governance requirements.

• Design and implement Machine Learning models

   for

  transaction monitoring

  , suspicious pattern detection, and fraud risk mitigation.

• Build fuzzy matching algorithms

   and

  entity resolution logic

   to enhance

  sanctions screening accuracy

   and reduce false positives.

• Perform customer segmentation

   using clustering techniques such as

  K-Means, RFM analysis

  to drive targeted engagement.

• Develop predictive models

   for customer behavior and product adoption using supervised ML techniques.
• Conduct

  feature engineering, statistical analysis

  , performance tuning, and model validation in alignment with compliance controls.
• Analyze transactional and behavioral datasets to provide

  data-driven insights

   supporting business and risk strategy.
• Prepare

  model documentation, validation reports

  , and audit-ready analytics summaries.
• Collaborate with

  Compliance, Digital Banking, and Technology

   teams to implement analytics solutions in production environments.

Job Responsibilities:

• Maintain

  operational viability

  of deployed AML models ensuring stable performance and minimal false positives.
• Lead

  end-to-end project delivery

   across data extraction, model development, testing, implementation, and monitoring.
• Ensure

  regulatory compliance

  and alignment with

  model risk governance

   standards.
• Communicate technical recommendations to

  non-technical business stakeholders

   effectively.

Desired Qualifications:

Domain Expertise

• Experience in

  Financial Crime / AML / Sanctions Screening / Fraud Risk Analytics

  .
• Familiarity with

  AML platforms

  , fuzzy match engines, and risk scoring frameworks.

Technical Skills

• Strong expertise in

  Python, SQL, Scikit-learn, XGBoost, Random Forest

  , and statistical modelling.
• Skilled in

  data preparation, feature engineering

  , and handling large datasets.
• Knowledge of visualization/reporting tools:

  Matplotlib, Tableau, Excel

  .

Soft Skills

• Strong

  analytical thinking

  ,

  documentation

  , and stakeholder communication.
• Ability to balance

  detection efficiency with operational practicality

  .

Interested can share their updated resume to anitha.mudaliyar@quantaleap.com