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Visa
Visa
Banku darbībaFinansesFintech
Visa ir globāls maksājumu tehnoloģiju uzņēmums, kas, izmantojot savu elektronisko maksājumu tīklu, apkalpo patērētājus, tirgotājus, finanšu iestādes un valdības. Tā platforma nodrošina kredīta, debeta un priekšapmaksas darījumus, kā arī maksājumu apstrādi, krāpšanas novēršanu, drošību, analītiku un citus pakalpojumus patērētājiem un uzņēmumiem. Visa izstrādā arī jaunus maksājumu risinājumus, tostarp ar mākslīgo intelektu iespējotus tirdzniecības risinājumus, un ar Visa Foundation starpniecību veicina finansiālo iekļaušanu.
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Vakances uzņēmumā

Senior Data Scientist, AML and Sanctions Screening

Develop and refine Visa’s anti-money laundering and sanctions screening models using machine learning and fuzzy matching. Improve detection quality and reduce false positives in global payments compliance.

INIndijaHibrīdiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuDatu zinātnieks
NumpyPandasPythonScikit-LearnSparkSQL

Apraksts

  • Analyze large datasets and turn business questions into actionable findings.
  • Examine structured and semi-structured data, including names, addresses, and identifiers.
  • Evaluate data quality, completeness, and suitability for sanctions screening.
  • Define and test features for matching and scoring.
  • Work with data engineering teams on data sourcing and transformation.
  • Develop and improve rules-based and fuzzy-matching sanctions screening models.
  • Adjust thresholds and scoring logic to increase detection accuracy and reduce false positives.
  • Analyze screening results and help design features that improve match quality.
  • Maintain audit-ready documentation of model logic, assumptions, and changes.
  • Track model performance and make improvements aligned with regulatory and Model Risk Management standards.
  • Design and run experiments to assess model performance using suitable metrics and statistical methods.
  • Coordinate testing, validation, audits, and regulatory reviews with Compliance, Model Risk Management, and Technology teams.
  • Validate models to confirm their accuracy, reliability, and compliance.
  • Work with stakeholders across business units and regulated entities to support Model Risk Management practices.
  • Document model architecture, implementation, and methodology.
  • Review model reports and share findings, insights, and recommendations with technical and business stakeholders.
  • Respond to ad hoc requests from business stakeholders.
  • Create end-user experiences that provide measurable value while remaining straightforward.

Prasības

  • At least 5 years of relevant experience with a bachelor’s degree, 2 years with an advanced degree, no experience required with a PhD, or at least 8 years of relevant experience.
  • Bachelor’s or master’s degree in engineering, economics, statistics, mathematics, or a related technical field.
  • At least 5 years of experience in data analysis, reporting, statistical analysis, research, data mining, trend analysis, or a related area.
  • Experience developing and implementing machine learning models using SAS, SQL, Python or R, Hive, and/or Spark.
  • Experience building predictive and descriptive statistical models with AI and machine learning methods such as logistic regression, random forests, SVMs, XGBoost, CNNs, or RNNs.
  • Expertise in sanctions screening and name matching.
  • Knowledge of anti-money laundering and counter-terrorist financing frameworks and financial crime compliance practices.
  • Understanding of global sanctions regimes, including OFAC, EU, UN, and UK guidelines.
  • Experience with rules-based or statistical models.
  • Familiarity with sanctions platforms such as Fircosoft, Comply, Advantage, World-Check, and Actimize.
  • Expertise in AI methods including machine learning, natural language processing, deep learning, and generative AI.
  • Experience with Python libraries such as pandas, NumPy, Matplotlib, and scikit-learn.
  • Knowledge of fuzzy matching, NLP-based n-grams, phonetics, tokenization, and similarity scoring.
  • Strong database management, data extraction, and data manipulation skills.
  • Ability to work effectively in a fast-paced, high-pressure environment with teams across the globe.
  • Willingness to work flexible hours across time zones.
  • Excellent communication, business writing, and stakeholder management skills.

Priekšrocības

  • Hybrid work arrangement.
  • Flexible schedule across time zones.

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