Senior Data Scientist
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Key skills for this role
About the Role
The Data Scientist position requires an experienced professional who is passionate about data modeling using machine learning and product development to help us build and maintain statistical & ML/AI based solutions in the AML & Sanctions, Compliance space, specifically supporting the Transaction Monitoring, Sanctions screening and Client Due Diligence programs. The candidate should be a motivated self-starter and quick learner willing to work in a high-pressure fast-paced environment and globally located teams. The candidate will be extensively involved in hands-on querying, analyzing, proposing and implementing optimization solutions, conduct user acceptance testing, and support business stakeholders’ enquiries on ad hoc basis. Successful candidate will be working in the Compliance Technology Operations (CTO) team which is part of the Global Ethics and Compliance organization
Key Skills for This Role
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Responsibilities
- Essential Functions:
- Strong analytical skills and compliance domain knowledge, with the ability to conduct large scale data analysis through all stages: understand business goal and strategy, formulate analytic approaches, perform data extraction and exploration, and translate results into actionable items
- Expertise in advanced techniques (Machine learning, natural language processing, deep learning), including exposure to Generative AI technologies and their applications. Experience with Python libraries such as pandas, numpy, matplot and Scikit
- Deployment of high-performance scalable AI/machine learning (ML) algorithms for building transaction monitoring and risk scoring solutions to improve the quality of alerts and investigation process
- Conduct periodic tuning of statistical and machine learning models using large-scale datasets to optimize models for performance, efficiency, and robustness
- Well versed with Compliance risk typologies and rules. Good knowledge and deployment experience of rules and typologies
- Design and conduct experiments to evaluate the model performance using appropriate metrics and statistical analysis to measure and interpret results
- Supervise and work with the Model Risk Management team as an independent contributor to support model validations across multiple business entities. Ensure the accuracy, reliability, and compliance of models by overseeing and conducting thorough validations
- Collaborate with internal stakeholders across business units and regulated entities to enhance alignment in implementing MRM policy/standards and promote MRM best practices
- Prepare technical documentation, including model architecture, implementation details and model methodology. Review model reports and communicate findings, insights, and recommendations to both technology and business stakeholders
- Essential Functions: - Strong analytical skills and compliance domain knowledge, with the ability to conduct large scale data analysis through all stages: understand business goal and strategy, formulate analytic approaches, perform data extraction and exploration, and translate results into actionable items - Expertise in advanced techniques (Machine learning, natural language processing, deep learning), including exposure to Generative AI technologies and their applications. Experience with Python libraries such as pandas, numpy, matplot and Scikit - Deployment of high-performance scalable AI/machine learning (ML) algorithms for building transaction monitoring and risk scoring solutions to improve the quality of alerts and investigation process - Conduct periodic tuning of statistical and machine learning models using large-scale datasets to optimize models for performance, efficiency, and robustness - Well versed with Compliance risk typologies and rules. Good knowledge and deployment experience of rules and typologies - Design and conduct experiments to evaluate the model performance using appropriate metrics and statistical analysis to measure and interpret results - Supervise and work with the Model Risk Management team as an independent contributor to support model validations across multiple business entities. Ensure the accuracy, reliability, and compliance of models by overseeing and conducting thorough validations - Collaborate with internal stakeholders across business units and regulated entities to enhance alignment in implementing MRM policy/standards and promote MRM best practices Prepare technical documentation, including model architecture, implementation details and model methodology. Review model reports and communicate findings, insights, and recommendations to both technology and business stakeholders
Qualifications
- Basic Qualifications: ∙ Bachelor's/Master’s Degree in Engineering, Economics, Statistics, Mathematics, or related technical discipline ∙ At least 8 years of experience in data science, analysis, reporting, statistical analysis, research, data mining, trend analysis etc. ∙ At least 8 years of experience in machine learning model development and implementation using tools like SAS, SQL, Python/R, Hive and/or Spark
- ∙ Building predictive and descriptive statistical models using AI/ML algorithms (e.g., logistic regression, random forests, SVMs, XGBoost, CNNs/RNNs)
- ∙ Compliance domain knowledge primarily for transaction monitoring, screening and client due diligence
- ∙ Excellent knowledge of database management, data extraction and data manipulation skills ∙ Superior communication, business writing and stakeholder management skills ∙ Self-motivated and proactive in talking to business partners/clients to identify and understand problem statements ∙ Passionate about building end-user experiences that deliver measurable value without increasing complexity
- ∙ Willing to work on a flexible schedule across different time zones
- Qualifications Basic Qualifications: ∙ Bachelor's/Master’s Degree in Engineering, Economics, Statistics, Mathematics, or related technical discipline ∙ At least 8 years of experience in data science, analysis, reporting, statistical analysis, research, data mining, trend analysis etc. ∙ At least 8 years of experience in machine learning model development and implementation using tools like SAS, SQL, Python/R, Hive and/or Spark ∙ Building predictive and descriptive statistical models using AI/ML algorithms (e.g., logistic regression, random forests, SVMs, XGBoost, CNNs/RNNs) ∙ Compliance domain knowledge primarily for transaction monitoring, screening and client due diligence ∙ Excellent knowledge of database management, data extraction and data manipulation skills ∙ Superior communication, business writing and stakeholder management skills ∙ Self-motivated and proactive in talking to business partners/clients to identify and understand problem statements ∙ Passionate about building end-user experiences that deliver measurable value without increasing complexity ∙ Willing to work on a flexible schedule across different time zones
About EXL
EXL is a global data and AI company that provides analytics, digital operations, and industry-specific services to enterprises in insurance, healthcare, banking, retail, media, and energy.
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