01 Aug
|
Important Company of the Sector
|
Bengaluru
01 Aug
Important Company of the Sector
Bengaluru
Summary:
The Risk Data Scientist plays a critical role within the BSA/AML/OFAC Model Development and Monitoring Team, driving the design, development, and ongoing evaluation of advanced transaction monitoring and screening models. This position is central to enhancing the accuracy and efficiency of fraud and risk detection systems, particularly in high -volume banking environments. The ideal candidate will leverage strong expertise in machine learning, statistical modeling, and data analytics to reduce false positives, improve model performance, and support compliance with regulatory standards. The role requires a blend of technical excellence, analytical rigor, and leadership, with responsibilities spanning model lifecycle management, cross -functional collaboration, and mentorship of junior analysts. Based in Bangalore, this is a full -time, in -office role requiring a deep understanding of risk analytics, data governance, and regulatory frameworks.
Responsibilities:
- Design and develop transaction monitoring scenarios to detect suspicious activities.
- Enhance scenario segmentation using advanced techniques such as clustering and pattern recognition.
- Conduct periodic tuning of threshold parameters through systematic sample analysis and evaluation.
- Build post -processing models using rare event logistic regression and machine learning to minimize false positives.
- Research and implement fuzzy logic -based algorithms for OFAC sanction screening and related processes.
- Develop NLP -driven models to improve the precision of screening outputs and reduce false alerts.
- Lead the implementation of models into production environments with robust version control and deployment practices.
- Establish and execute ongoing monitoring plans to assess model performance and compliance.
- Maintain comprehensive documentation of model development, deployment, and validation processes.
- Collaborate with model validation teams to ensure adherence to internal and external standards.
- Deliver timely ad hoc analyses in response to business or regulatory requests.
- Prepare and present actionable insights and strategic recommendations to senior stakeholders.
- Uphold data accuracy, governance, and transparency across all analytical workflows.
- Mentor and guide 3–4 junior analysts, including task assignment, quality review, and professional development.
Requirements
- Bachelor’s degree in Statistics, Data Science, Operations Research, Industrial Engineering, Mathematics, or Physics, with 6 years of relevant experience.
- Master’s degree in a related field with 4 years of relevant experience.
- PhD in Statistics, Operations Research, Industrial Engineering, Mathematics, or Physics with 2 years of relevant experience.
- 6–8 years of experience for Lead; 9+ years for Manager roles.
- Proven experience in risk and fraud analytics, with a banking or financial services background preferred.
- Expertise in SQL and Python for data analysis, modeling, and automation.
- Robust foundation in machine learning, classification models, and statistical modeling.
- Experience with the CDSW platform and software development lifecycle practices.
- Familiarity with web scraping and advanced data sourcing techniques.
- Demonstrated ability to translate complex analytical results into clear, strategic insights for non -technical audiences.
- Exceptional communication, coordination, and mentorship skills.