Fraud Risk AI Scientist Job at Robert Half (Charlotte)

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, AI & Model Risk

It all started with an idea at Block in 2013. Initially built to take the pain o...

Location

United States , Bay Area

Salary:

139000.00 - 225000.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

A minimum of 5 years of related experience with a Bachelor’s degree in a quantitative field
or 3 years and a Master’s degree
or a PhD without experience
or equivalent work experience in risk management, model risk management, or AI risk management
Proficiency in Python or similar languages for evaluating AI system behavior, writing test scripts, or analyzing model outputs
Strong understanding of generative AI architectures
Including LLMs, transformer models, RAG systems, and agentic AI, plus hands-on experience interacting with and critically evaluating these systems, sufficient to assess design decisions, output quality, and limitations
Understanding of interagency model risk management principles, including SR 26-2
Knowledge of AI testing methodologies, ex. functional testing, bias testing, adversarial testing, and performance monitoring plus familiarity with data privacy and security principles (encryption, access controls, data classification)
Excellent written and verbal communication and the ability to translate complex technical AI concepts for non-technical stakeholders, senior management, and regulators

Job Responsibility

Lead end-to-end AI Risk Assessments for generative AI and LLM use cases across the Bank
Embedding in Block's enterprise-wide GenAI review process, coordinating cross-functional SMEs (Legal, Compliance, InfoSec, Data Governance, MRM, ERM, BRC, TPRM, Financial Crimes), and managing timelines to ensure reviews are completed within SLA
Review AI system design and documentation
Including retrieval sources, assumptions, limitations, fallback plans, guardrail configurations, and change management procedures — across banking use cases such as fraud detection, BSA/AML compliance, credit decisioning, and customer-facing applications, ensuring governance controls are commensurate with each use case's risk profile
Assess pre-deployment testing for adequacy inclusive of output integrity, hallucination detection, boundary and edge case testing, ethical and safety guardrails, bias testing, A/B testing, volume testing, and UAT — designing and conducting independent testing as needed
Evaluate ongoing monitoring plans for comprehensiveness - including accuracy, hallucination rates, drift detection, sensitive data controls, reliability metrics, CSAT, acceptable performance ranges, and documented remediation procedures
Develop and maintain templates, tools, and procedures to support the effectiveness and scalability of the AI Risk Governance Program
Monitor the evolving regulatory landscape for AI in banking — including FFIEC IT Examination Handbook standards, FDIC Financial Institution Letters, interagency statements, and the anticipated RFI on AI model risk management referenced in SR 26-2 — and incorporate emerging guidance into the AI risk governance program
support SFS's response to regulatory inquiries as needed

What we offer

Remote work
medical insurance
flexible time off
retirement savings plans
modern family planning

Fulltime

Senior Data Scientist, AI & Model Risk

It all started with an idea at Block in 2013. Initially built to take the pain o...

Location

United States , New York

Salary:

139000.00 - 225000.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

A minimum of 5 years of related experience with a Bachelor’s degree in a quantitative field
or 3 years and a Master’s degree
or a PhD without experience
or equivalent work experience in risk management, model risk management, or AI risk management
Proficiency in Python or similar languages for evaluating AI system behavior, writing test scripts, or analyzing model outputs
Strong understanding of generative AI architectures
Including LLMs, transformer models, RAG systems, and agentic AI, plus hands-on experience interacting with and critically evaluating these systems, sufficient to assess design decisions, output quality, and limitations
Understanding of interagency model risk management principles, including SR 26-2
Knowledge of AI testing methodologies, ex. functional testing, bias testing, adversarial testing, and performance monitoring plus familiarity with data privacy and security principles (encryption, access controls, data classification)
Excellent written and verbal communication and the ability to translate complex technical AI concepts for non-technical stakeholders, senior management, and regulators

Job Responsibility

Lead end-to-end AI Risk Assessments for generative AI and LLM use cases across the Bank
Embedding in Block's enterprise-wide GenAI review process, coordinating cross-functional SMEs (Legal, Compliance, InfoSec, Data Governance, MRM, ERM, BRC, TPRM, Financial Crimes), and managing timelines to ensure reviews are completed within SLA
Review AI system design and documentation
Including retrieval sources, assumptions, limitations, fallback plans, guardrail configurations, and change management procedures — across banking use cases such as fraud detection, BSA/AML compliance, credit decisioning, and customer-facing applications, ensuring governance controls are commensurate with each use case's risk profile
Assess pre-deployment testing for adequacy inclusive of output integrity, hallucination detection, boundary and edge case testing, ethical and safety guardrails, bias testing, A/B testing, volume testing, and UAT — designing and conducting independent testing as needed
Evaluate ongoing monitoring plans for comprehensiveness - including accuracy, hallucination rates, drift detection, sensitive data controls, reliability metrics, CSAT, acceptable performance ranges, and documented remediation procedures
Develop and maintain templates, tools, and procedures to support the effectiveness and scalability of the AI Risk Governance Program
Monitor the evolving regulatory landscape for AI in banking — including FFIEC IT Examination Handbook standards, FDIC Financial Institution Letters, interagency statements, and the anticipated RFI on AI model risk management referenced in SR 26-2 — and incorporate emerging guidance into the AI risk governance program
support SFS's response to regulatory inquiries as needed

What we offer

Remote work
medical insurance
flexible time off
retirement savings plans
modern family planning

Fulltime

Data Scientist II - Fraud & Risk

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

Location

United States

Salary:

140000.00 - 170000.00 USD / Year

Socure

Expiration Date

Until further notice

Requirements

Bachelor’s degree with substantial related experience, Master’s degree with relevant experience, or equivalent work background in Computer Science, Statistics, Mathematics, Engineering, or a related field
2-4 years of hands-on experience developing and deploying deep learning models (such as transformers, CNNs, and LSTMs)
Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images
Proficiency in Python and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Foundational understanding of machine learning algorithms, model evaluation techniques, and data pipeline development
Experience with model deployment and monitoring in production environments
Strong problem-solving skills, with the ability to work independently on straightforward tasks and contribute effectively to project objectives
Demonstrated ability to collaborate in a diverse, cross-functional team environment
Excellent written and verbal communication skills

Job Responsibility

Design, develop, and implement advanced deep learning models, including transformers, CNNs, and LSTMs, 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
Take ownership of assigned tasks, executing technical and functional activities to support project goals with minimal supervision
Participate in all stages of the machine learning lifecycle: data exploration, feature engineering, model training, evaluation, and deployment
Collaborate effectively across teams, sharing knowledge and learning from diverse perspectives to drive results
Make routine technical decisions and contribute to functional objectives through productive and proactive engagement
Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems
Communicate results and insights clearly to both technical and non-technical audiences

What we offer

Offers Equity
Offers Bonus

Fulltime

Avp Fraud Analytics - Data Scientist & Gen Ai

The Specialized Analytics Sr Anlst is a seasoned professional role. Applies in-d...

Location

India , Pune

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Bachelor's or Master's degree in computer science, Data Science, Machine Learning, or a related field. A Ph.D. is a plus
8+ years of experience in machine learning and deep learning, with a focus on generative AI solution design and development
Strong proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras
Strong background of Prompt Engineering, building agentic AI / AI Agents, API / MCPs for large scale automations in banking domain
Experience with natural language processing (NLP) and natural language generation (NLG)
Proven track record of building and deploying generative models based solutions in production environments particularly using RAG frameworks
Solid understanding of machine learning algorithms, data structures, and software engineering principles
Excellent problem-solving skills and the ability to work independently and as part of a team
Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders

Job Responsibility

Design, Develop and deploy generative models for various applications in Fraud Operations
RAG Frameworks – Able to customize and fine-tune existing RAG frameworks or design new RAG to meet project requirements
Design and Develop POC / full scale solutions on various automations in Operations area including Conversational AI, Muti Agent Systems for multiple services
Responsible for development and deployment of Machine Learning / Deep Learning based models
Collaborate with cross-functional team to understand business requirements and translate them into AI solutions
Conduct research to advance the state-of-the art in generative modeling and stay up to date with latest advancements in the field
Optimize and fine-tune models for performance, scalability, and robustness
Implement and maintain AI pipelines and infrastructure to support model training and deployment
Perform data analysis and preprocessing to ensure high-quality input for model training
Implement and maintain AI pipelines and infrastructure to support model training and deployment. - Perform data analysis and preprocessing to ensure high-quality input for model training

Fulltime

Data Scientist - Risk Analytics

We're looking for a Risk Analyst to join our Fraud & Financial Crime Team. You w...

Location

United Kingdom , London

Salary:

Not provided

Capital on Tap

Expiration Date

Until further notice

Requirements

At least three years of risk analysis experience ideally including credit cards, fraud or fincrime
Highly analytical and comfortable conducting complex analysis using SQL and Python
Exceptional detail orientated, problem solving skills and the ‘can do’ attitude to thrive in a fast paced, high growth environment
Excellent collaboration skills and a natural team player
Strong verbal communication skills including the ability to clearly explain complex concepts to other analysts, business stakeholders and senior leadership
2.1 or above at degree level, preferably in Economics or STEM subject

Job Responsibility

Owning, monitoring and continually optimising our fraud detection rules
Applying advanced analytics to maximise the efficiency and effectiveness of our Financial Crime detection processes
Supporting the launch of new products and balancing the need for robust fraud and financial crime controls whilst maintaining a positive customer experience
Working with external vendors to continually evaluate innovative or alternative products and tools
Proactively championing best use of AI to accelerate delivery of analytical output and as an integral part of our business solutions
Present and actively collaborate with a wide group of business stakeholders including Operations, Credit, Senior Management, and external business partners

What we offer

Private Healthcare including dental and opticians services through Vitality
Worldwide travel insurance through Vitality
Anniversary Rewards (£250, £500, £750, 4-week fully paid sabbatical)
Salary Sacrifice Pension Scheme up to 7% match
28 days holiday (plus bank holidays)
Annual Learning and Wellbeing Budget
Enhanced Parental Leave
Cycle to Work Scheme
Season Ticket Loan
6 free therapy sessions per year

Fulltime

Data Scientist & Gen AI Vice President

This role is a senior position where we are seeking a highly experienced and str...

Location

India , Haryana

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

10+ years of hands-on experience in data science, or AI/ML roles
7+ years’ experience in statistical analysis with working knowledge of at least one of the following statistical software packages: Python (Must), Hive, Spark, SAS
Strong quantitative, analytical, and problem-solving skills
knowledge of probability theory, statistics, mathematical finance, econometrics, numerical methods
2+ years of hands-on experience specifically with generative AI or LLMs
Strong understanding of statistical concepts and modelling techniques including traditional and advanced ML algorithms
Strong programming skills in Python, and familiarity with libraries like Transformers, LangChain, LlamaIndex, PyTorch, or TensorFlow
Working knowledge of retrieval-augmented generation (RAG) pipelines and vector databases
Understanding of MLOps / LLM Ops, model evaluation, prompt tuning, and deployment pipelines
Experience building applications with OpenAI, Anthropic Claude, Google Gemini, or open-source LLMs

Job Responsibility

Lead the design and implementation of generative AI use cases, from ideation to production
Build and tune LLM-based applications using platforms like Vertex, GPT, Hugging Face, etc
Create robust prompt engineering strategies and reusable prompt templates
Integrate generative AI with enterprise applications using APIs, knowledge graphs, vector databases (e.g., PG Vector, Pinecone, FAISS, Chroma), and orchestration tools
Collaborate with Tech and business teams to identify opportunities and build solutions
Responsible for model development, validation and testing of fraud detection models, including statistical analysis, data validation and model performance evaluation
Ensure compliance with regulatory requirements and industry best practices in fraud detection and model validation
Responsible for documenting the model development documents for MRM approvals and governance purposes
Stay current on GenAI trends, frameworks (LangChain, LlamaIndex), and research
Mentor junior team members and promote a culture of experimentation and learning

Fulltime

Applied Scientist III, Buyer Risk Prevention

Do you want to lead the development of advanced machine learning systems that pr...

Location

India , Bengaluru

Salary:

Not provided

Amazon

Expiration Date

Until further notice

Requirements

3+ years of building machine learning models for business application experience
PhD, or Master's degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning

Job Responsibility

Lead the end-to-end scientific strategy for large-scale fraud and risk modeling initiatives
Define problem statements, success metrics, and long-term modeling roadmaps in partnership with business and engineering leaders
Design, develop, and deploy highly scalable machine learning systems in real-time production environments
Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies to automate and transform risk evaluation
Influence system architecture and partner with engineering teams to ensure robust, scalable implementations
Establish best practices for experimentation, model validation, monitoring, and lifecycle management
Mentor and raise the technical bar for junior scientists through reviews, technical guidance, and thought leadership
Communicate complex scientific insights clearly to senior leadership and cross-functional stakeholders
Identify emerging scientific trends and translate them into impactful production solutions

Select Country

Fraud Risk AI Scientist

Job Responsibility

Requirements

What we offer

Looking for more opportunities?