Senior Data Scientist - Financial Crime

1w1 week ago

NTT DATA

London, GB · Full-time · £90,000 – £130,000

About this role

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. We are looking for an experienced Senior Data Scientist with strong expertise in Python, PySpark, and advanced analytics, along with a solid understanding of Financial Crime, Fraud Monitoring, and AML concepts. The ideal candidate will work on large-scale data to build, enhance, and optimize analytical and machine learning models used for fraud detection and financial crime prevention.

You will design, develop, and deploy data science and machine learning models for fraud detection, transaction monitoring, and financial crime use cases. Analyze large, complex datasets using Python and PySpark in distributed data environments, while building end-to-end analytics pipelines including data ingestion, feature engineering, model training, and validation. Apply statistical analysis, ML techniques, and pattern recognition to identify suspicious behaviors and emerging fraud typologies.

Collaborate with business, compliance, and technology teams to translate financial crime requirements into analytical solutions. Monitor model performance, perform tuning, and ensure model stability and regulatory alignment. Document models, methodologies, and assumptions for internal governance and audit requirements.

Stay updated on financial crime trends, fraud patterns, and regulatory expectations as part of an inclusive, adaptable, and forward-thinking organization. NTT DATA is a $30 billion business and technology services leader serving 75% of the Fortune Global 100, with unmatched capabilities in AI, cloud, security, and more. Join experts in more than 50 countries and access a robust ecosystem of innovation centers.

Whenever possible, we hire locally to NTT DATA offices or client sites for timely support. Many positions offer remote or hybrid work options, subject to client requirements, with in-office attendance as needed for meetings or events. We remain committed to flexibility for clients and employees.

Requirements

5+ years of experience in Data Science, Analytics, or a related role
Strong proficiency in Python (NumPy, Pandas, Scikit-learn, etc.)
Hands-on experience with PySpark / Spark for large-scale data processing
Solid understanding of Financial Crime domains including Fraud Monitoring, Transaction Monitoring, AML / CTF concepts, and Customer risk and suspicious activity patterns
Experience building and validating machine learning models (supervised & unsupervised)
Strong knowledge of data preprocessing, feature engineering, and model evaluation
Ability to communicate complex analytical findings to non-technical stakeholders

Responsibilities

Design, develop, and deploy data science and machine learning models for fraud detection, transaction monitoring, and financial crime use cases
Analyze large, complex datasets using Python and PySpark in distributed data environments
Build end-to-end analytics pipelines including data ingestion, feature engineering, model training, and validation
Apply statistical analysis, ML techniques, and pattern recognition to identify suspicious behaviors and emerging fraud typologies
Collaborate with business, compliance, and technology teams to translate financial crime requirements into analytical solutions
Monitor model performance, perform tuning, and ensure model stability and regulatory alignment
Document models, methodologies, and assumptions for internal governance and audit requirements
Stay updated on financial crime trends, fraud patterns, and regulatory expectations

Benefits

Part of NTT DATA, a $30 billion business and technology services leader serving 75% of the Fortune Global 100
Global Top Employer with experts in more than 50 countries
Access to a robust ecosystem of innovation centers and established and start-up partners
Part of NTT Group, which invests over $3 billion each year in R&D
Remote or hybrid work options, subject to client requirements