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Visa is seeking a Senior Data Scientist to build and maintain ML/AI solutions for AML sanctions screening and name-matching. You will work on fuzzy matching, NLP, and rules-based models in a fast-paced, globally distributed team.
The role requires 5+ years in data analysis and ML model development, with experience in SAS/SQL/Hive/Spark and Python/R. This hybrid position is based in Bengaluru with cross-time-zone collaboration.
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.
At Visa, you''ll have the opportunity to create impact at scale tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
Join Visa and do work that matters to you, to your community, and to the world. Progress starts with you.
The Senior Data Scientist position requires an experienced professional who is passionate about data analysis, 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 Sanctions Screening. Additionally, experience in techniques including fuzzy matching, NLP based n-grams methodology, phonetics, tokenization, and similarity scoring will be desirable.
The candidate is expected to demonstrate expertise in sanctions screening and name-matching, along with experience working with rules-based or statistical models and familiarity with major sanctions platforms such as Fircosoft, ComplyAdvantage, World-Check, and Actimize, etc. will be preferable.
The candidate will be expected to have understanding of global sanctions regimes, including OFAC, EU, UN, and UK guidelines. They should demonstrate strong knowledge of Anti-Money Laundering (AML) and Counter Financing of Terrorism (CFT) frameworks, as well as financial crime compliance practices.
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
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
Bachelor''s/Masters Degree in Engineering, Economics, Statistics, Mathematics, or related technical discipline
At least 5 years of experience in data analysis, reporting, statistical analysis, research, data mining, trend analysis etc.
At least 5 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). Additionally, experience in techniques including fuzzy matching, NLP based n-grams methodology, phonetics, tokenization, and similarity scoring will be desirable.
Expertise in sanctions screening and name-matching, along with experience working with rules-based or statistical models and familiarity with major sanctions platforms
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
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.