Fraud Data Scientist Job at Barclays (Northampton)

Data Scientist - Fraud Detection

Are you looking for a new challenge? Fancy helping us shape the future of motor ...

Location

Spain , Madrid

Salary:

Not provided

Prima

Expiration Date

Until further notice

Requirements

Extensive experience (3+ years) in data science or applied machine learning, leading end-to-end initiatives in complex technical domains and delivering measurable business impact
Strong analytical and quantitative mindset able to translate data into insights, assess model performance, and guide decision-making with evidence and clarity
Structured problem solver skilled at framing ambiguous challenges, defining success metrics, and communicating results to both technical and non-technical audiences
Strong Python programming skills, especially in the data domain, and fluent use of Git
Knowledge of Spark, SQL or any other data-oriented programming language and proficiency with standard data wrangling and modeling libraries (Pandas, Sklearn, Keras, XGBoost, LightGBM, etc.)

Job Responsibility

Design and improve fraud detection systems that prioritize high-risk claims, optimizing the trade-off between detection accuracy and operational efficiency
Collaborate across teams and functions, working closely with fraud analysts, engineers, and product managers
Develop deep expertise in fraud dynamics, identifying emerging fraud patterns, understanding how they evolve across the insurance lifecycle, and translating these insights into effective detection and prevention strategies, for example identifying suspicious networks of related claims, synthetic entities, or anomalous behavioral patterns

What we offer

Hybrid working, with a mix of home and office days
Up to 30 days per year work from anywhere
Access to learning resources, mentorship and a growth plan tailored to you
Private healthcare
Gym discounts
Wellbeing programs
Mental health support

Fulltime

Staff Data Scientist (Fraud, Risk)

Uber is looking for an experienced and motivated Scientist to join our Global Sa...

Location

Brazil , Sao Paulo

Salary:

Not provided

Uber

Expiration Date

Until further notice

Requirements

Senior and/or Staff seniority working as a Data Scientist, Applied Scientist, or Machine Learning Engineer
Experience building and deploying Binary Classification systems in production for large-scale, high-stakes applications (e.g., Fraud, Safety, or Risk)
Deep experience in Experimental Design beyond classical A/B testing, including Quasi-experiments (Diff-in-Diff, Synthetic Control) or Marketplace experiments (Switchbacks)
Expertise in handling Extreme Class Imbalance and optimizing models for rare event detection
Experience using Python and SQL to work with massive, high-dimensional data sets at scale
Solid foundation in Statistical Methodologies such as probability calibration, sampling, and hypothesis testing

Job Responsibility

Conduct thorough analyses of large, imbalanced datasets to identify trends, patterns, and opportunities for improving safety incident detection
Design, implement, and optimize binary classification models and algorithms to predict the probability of high-severity incidents
Generate actionable insights from risk data and communicate findings to stakeholders, balancing safety interventions with marketplace growth
Work as a thought expert for your cross-functional partners (Product, Ops, and Engineering), pushing the boundaries of how Uber defines and mitigates risk
Design complex experiments (Diff-in-Diff, Synthetic Controls) and interpret results to draw impactful conclusions in a marketplace environment where classical A/B testing is often not feasible
Define how your cross-functional team measures success by developing Safety & Risk metrics (e.g., Recall, Precision-Recall AUC, Probability Calibration) in partnership with global stakeholders
Stay current with the latest advancements in Supervised Learning, Causal Inference, and Anomaly Detection

Fulltime

Senior Data Scientist - Fraud

The Data team within Plaid’s Fraud organization builds the machine learning syst...

Location

United States , Seattle

Salary:

214800.00 - 286800.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

5+ years of total experience
At least 2–3 years working deeply with product analytics, machine learning, experimentation, or data-driven products
Strong proficiency in SQL and Python
Hands-on experience with product analytics, experimentation frameworks, or backtesting methodologies
Skilled in designing, building, and maintaining dashboards and core product performance metrics
Capable of designing and interpreting backtests or offline evaluations for ML and rules-based systems
Excellent communicator with strong stakeholder-management skills across diverse teams

Job Responsibility

Work at the intersection of product analytics, machine learning, and fraud/risk to drive meaningful product improvements
Own the metrics, dashboards, and experimentation frameworks that inform product strategy and decision-making
Analyze complex datasets to uncover clear, actionable insights that shape product direction
Partner with go-to-market teams to demonstrate the technical and business value of our products to customers

Fulltime

Data Scientist, Fraud

We are looking for an ambitious Data Scientist to join our Fraud and Payments te...

Location

Estonia , Tallinn

Salary:

Not provided

Bolt

Expiration Date

Until further notice

Requirements

Exceptional knowledge of machine learning algorithms, statistical inference, and autonomous decision-making systems
Enthusiasm to collaborate with different roles in product, analytics and engineering to identify problems, explore trends and untap growth opportunities
Passion for continuous learning and a collaborative mindset, valuing open technical discussions and peer-to-peer knowledge sharing
Mastery in Python and SQL
Previous experience in fraud detection, payment optimization or related financial services is a plus
Strong academic background in a quantitative field

Job Responsibility

Working with a technical stack consisting of Python, Docker, SageMaker, Airflow and Databricks
Building and improving fraud prediction models using different predictive approaches
Exploring techniques that can improve the way we manage payments, including Causal and Reinforcement Learning
Handling the entire lifecycle from project conceptualization and notebook prototyping to productizing and maintaining a machine learning based solution or other automation that might be serving hundreds of millions of users in production
Leveraging our in-house data and model platform that allows you to launch new projects in a matter of days
Deploying and A/B testing solutions for millions of users, enabling fast feedback and measurable added value to customers

What we offer

Get a rewarding salary and stock option package that lets you focus on doing your best work
Enjoy the flexibility of working in a hybrid mode
Take care of your physical and mental health with our wellness perks

Senior Risk & Fraud Data Scientist, Algorithm

As a Senior Machine Learning engineer, you will tackle challenging machine learn...

Location

Singapore , Singapore

Salary:

Not provided

Airwallex

Expiration Date

Until further notice

Requirements

At least 3+ years experienced with common ML libraries, such as scikit-learn, TensorFlow, PyTorch, Keras, etc.
Bachelor’s or above degree in Computer Science, Engineering, or a related technical field.
Proficient in coding language such as Python and SQL.
Experience in payment risk or international e-commerce risk is a plus.
Experience in applying LLMs to real-time risk management is a plus.

Job Responsibility

Analyze business requirements and translate them into machine learning problems
Work on data engineering, feature engineering, model training, and deployment
Identify issues and propose effective solutions through regular analysis
Develop machine learning platforms and tools to streamline ML workflows at Airwallex
Collaborate with cross-functional teams to apply models that solve business problems

Fulltime

Staff Data Scientist - Fraud & Risk

We are seeking a skilled and motivated Staff Data Scientist to join our Fraud & ...

Location

United States

Salary:

140000.00 - 210000.00 USD / Year

Socure

Expiration Date

Until further notice

Requirements

Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field
or equivalent professional experience
8+ years of experience in data science, machine learning, or related fields, ideally in a high-growth tech or fintech environment
Experience in fraud prevention, risk modeling, or identity verification
Years of hands-on experience developing and deploying deep learning models (such as transformers, CNNs/RNNs, and graph learning)
Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images
Strong proficiency in Python, SQL, and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Deep understanding of machine learning algorithms, model evaluation techniques, and data pipeline development
Experience with model deployment and monitoring in production environments (specific experience with real-time model inferencing is a plus)
Demonstrated ability to proactively deliver complex outcomes, mentor others, and influence cross-functional decisions

Job Responsibility

Design, develop, and implement advanced deep learning models, including transformers, CNNs/RNNs, and graph learning algorithms, to address complex fraud and risk challenges
Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images
Lead the end-to-end machine learning lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and monitoring in production environments
Take ownership of project outcomes, data quality, and delivery timelines
proactively escalate issues and work collaboratively to resolve challenges
Mentor and share knowledge with peers and junior data scientists, fostering a culture of experimentation, rapid iteration, and continuous learning
Collaborate cross-functionally with Product, Engineering, and Risk teams to define data requirements and drive insights that guide strategic decisions
Conduct in-depth research to explore new data sources and develop novel algorithms that advance the state of the art in fraud detection
Present findings and recommendations to technical and executive stakeholders with clarity and influence
Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems

What we offer

Offers Equity
Offers Bonus

Fulltime

Senior Data Scientist, Fraud

Join us in building the future of finance. Our mission is to democratize finance...

Location

United States , Menlo Park

Salary:

187000.00 - 220000.00 USD / Year

Robinhood

Expiration Date

Until further notice

Requirements

5+ years of experience in data science or applied ML, with a focus on fraud detection or risk mitigation
Advanced proficiency in Python and SQL
experience with ML frameworks like XGBoost, LightGBM, or TensorFlow
Strong statistical acumen with experience in anomaly detection, pattern recognition, and A/B testing
Excellent communication skills and ability to influence decision-making across technical and non-technical audiences
A collaborative mindset and proactive approach to navigating ambiguity in fast-paced environments

Job Responsibility

Design and deploy fraud detection models to protect Robinhood users and assets in real time
Analyze behavioral data to uncover emerging fraud vectors and support rapid incident response
Develop robust data pipelines and monitoring systems to ensure model accuracy and reliability
Partner with engineering and product teams to implement safeguards and user-facing features
Guide experimentation strategy and contribute to long-term fraud prevention roadmap

What we offer

Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
100% paid health insurance for employees with 90% coverage for dependents
Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
Employer-paid life & disability insurance, fertility benefits, and mental health benefits
Time off to recharge including company holidays, paid time off, sick time, parental leave, and more
Exceptional office experience with catered meals, events, and comfortable workspaces

Fulltime

Data Scientist - Fraud prevention

You will be in charge of developing next-generation fraud prevention systems by ...

Location

Italy , Milan

Salary:

Not provided

Subbyx

Expiration Date

Until further notice

Requirements

Minimum of 4 years of experience in a similar role in Data Science or Machine Learning
Degree in Mathematics, Physics, Computer Science, Statistics or similar
High proficiency in Python
Experience with Statistical Analysis and Machine Learning
Analytical and data oriented
Excellent knowledge of the English language
Team-work and goal-oriented approach
Ability to work independently with high problem solving skills

Job Responsibility

Train deploy and maintain sophisticated Machine Learning models to spot and block potential frauds
Develop, enhance, and optimize methods for data acquisition, extraction, and processing to ensure the availability of high-quality, relevant data for fraud prevention
Research and experiment alternative approaches to combat fraudulent attempts
Analyze and quantify behavioural patterns of our customer base in order to identify relevant patterns
Apply pattern recognition and anomaly detection techniques to identify unusual activities and prevent potential fraud across our platform

What we offer

Competitive salary
Welfare
Stock options and performance bonuses
Meal vouchers
Welfare & Wellbeing
Insurance policy
Training
Smart working
Women’s wellbeing
Electric mobility

Fulltime

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Fraud Data Scientist

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