Data Scientist

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

Lead Data Scientist

Prism is seeking a Lead Data Scientist who will make high-impact, hands-on contr...

Location

United States , NYC or San Diego (La Jolla/UTC)

Salary:

140000.00 - 160000.00 USD / Year

Prism Data

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Statistics, Data Science, Math, Industrial Engineering, or similar quantitative discipline required
4+ years of experience as a Data Scientist or Statistician, preferably in credit risk or financial services
Research & development of new attributes, models, decision strategies, and/or analytic capabilities
Customer-facing testing of data or analytic solutions (e.g., credit risk scores, alternative data, fraud prevention, etc.)
Collaboration with business teams to understand and address business problems
Modeling experience in the latest AI and machine learning approaches
Mastery of rudimentary modeling approaches (e.g., regression, decision trees)
Knowledge of data labeling/categorization, feature development and selection, model design and training, testing, coding, implementation, monitoring, and governance
Financial services industry data expertise, including types of data sources applicable to different types of business decisions based on regulatory factors
Experience evaluating alternative statistical approaches, including review of academic papers on new techniques and ideas, and justifying which approach is best suited for which problems and why

Job Responsibility

Maintain and advance existing analytical product suite
Enhance core cash flow underwriting offerings as new data elements become available
Develop next-generation versions of products to boost stability, predictive accuracy, and relevancy to emerging use cases
Develop new products for new market opportunities using novel data assets
Demonstrate best practices in transparent modeling approaches to enable easy client adoption
Support sales, revenue attainment, and thought leadership
Conduct proof of concept analyses of the efficacy of Prism products in the context of clients’ business problems, and present results and insights
Support new and existing clients by guiding them on score cutoffs and the use of powerful custom attribute sets for their business
Educate clients on technical product knowledge
Contribute analysis to thought leadership content delivered by Prism executives in white papers and industry conferences

What we offer

medical
dental
vision
401(k)
equity-based compensation

Fulltime

The Specialized Analytics Sr Anlst role applies in-depth disciplinary knowledge,...

Location

India , Bengaluru; Pune

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

8+ years of experience in machine learning and deep learning, with a focus on generative models
Strong proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras
Experience working with Model Risk Management team for model approval and governance related work
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, few shot prompts, etc.
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

Job Responsibility

Design, Develop and deploy generative AI based solutions for various Fraud prevention area
RAG Frameworks – Able to customize and fine-tune existing RAG frameworks or design new RAG to meet project requirements
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
Strong experience in prompt engineering
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
Mentor junior team members and provide technical guidance
Write and maintain comprehensive documentation for models and algorithms

Fulltime

Commercial Card Fraud Innovation Strategy Leader

The Commercial Card Fraud Strategy Leader leads the end‑to‑end strategy, analyti...

Location

United States , Columbus; Philadelphia; Chicago; Short Hills; Glen Allen; Westwood; Irving; Pittsburgh; Mason; Melville; Ohio; Remote

Salary:

146000.00 - 178000.00 USD / Year

Citizens Bank

Expiration Date

April 30, 2026

Requirements

10+ years of experience in fraud strategy, fraud prevention, data analytics, or risk management
5+ years of experience in fraud risk management at commercial card issuers
Deep expertise in identity and payment fraud methods, tools, and processes for prevention, detection, and fraud operations
Advanced proficiency in data science techniques, including machine learning, predictive modeling, and statistical analysis
Experience with fraud detection platforms, rule engines, and data visualization tools
Strong understanding of payment processing systems, card networks, and risks specific to card transactions and corporate expense management
Excellent analytical, organizational, and problem-solving skills
Strong verbal and written communication skills, with the ability to present requirements and issues clearly
Ability to lead multiple projects simultaneously, prioritize effectively, and thrive in a fast-paced, evolving environment
Proficiency in MS Office suite and analytical tools such as Python, R, SQL, and/or SAS

Job Responsibility

Lead end-to-end reviews of current fraud and credit risk management capabilities, strategies, and controls
Oversee and monitor the Commercial Credit Card portfolio to reduce credit and fraud losses, mitigate employee misuse, and balance customer experience
Identify risks, develop controls, and evaluate their effectiveness, escalating issues as appropriate
Deliver timely escalation of risk issues to senior management and collaborate on action plans
Build and mentor a team of data scientists and analysts to develop and implement advanced machine learning and statistical models for fraud detection and prevention
Drive portfolio fraud analytics across customer segments, providing actionable insights for risk strategies
Develop predictive models to monitor and mitigate emerging fraud threats, integrating real-time detection with engineering and IT teams
Use data-driven insights to recommend improvements to fraud prevention systems and technologies
Develop a comprehensive fraud risk management program for Commercial Card and Expense products, including key indicators for tracking and reporting
Partner with internal stakeholders, external vendors, and customers to launch and update risk controls across products

What we offer

Competitive pay
comprehensive medical, dental and vision coverage
retirement benefits
maternity/paternity leave
flexible work arrangements
education reimbursement
wellness programs
paid time off policy exceeds mandatory requirements

Fulltime

Sr./Staff Data Scientist

Shape the future of trust in the age of AI. At Oscilar, we're building the most ...

Location

Canada

Salary:

Not provided

Oscilar

Expiration Date

Until further notice

Requirements

3+ years of experience in data science, machine learning, or a related field, with a focus on fraud prevention and/or anti-money laundering
Proficiency in Python
Strong knowledge of machine learning algorithms and statistical techniques, with a focus on their application in fraud detection
Experience working with large datasets using distributed systems like Apache Spark and Dask, handling data-related challenges such as data cleaning, data quality, and data transformation and feature engineering at scale
Excellent analytical and problem-solving skills, with the ability to derive actionable insights from complex data
Strong communication skills, with the ability to explain complex concepts and findings to both technical and non-technical audiences
Ability to work independently and collaboratively in a fast-paced, dynamic startup environment

Job Responsibility

Develop and implement advanced fraud detection models, leveraging machine learning and statistical techniques, to identify and prevent fraudulent activities across our platform
Collaborate with cross-functional teams, including engineering, product, and operations, to design and implement fraud detection systems and processes
Analyze large volumes of data to identify patterns, trends, and anomalies indicative of fraudulent behavior, and develop data-driven insights to improve fraud prevention strategies
Evaluate the performance of existing fraud detection models and systems, and continuously optimize and update them to adapt to changing fraud trends and tactics
Stay up-to-date with the latest trends and advancements in fraud detection, data science, and machine learning, and apply this knowledge to enhance our fraud prevention capabilities
Communicate complex data analysis and model performance results to both technical and non-technical stakeholders, driving data-driven decision-making across the organization
Ensure data privacy and security compliance in all aspects of fraud detection and data analysis

What we offer

Competitive salary and equity packages, including a 401k
Remote-first culture — work from anywhere
100% Employer covered comprehensive health, dental, and vision insurance with a top tier plan for you and your dependents (US)
Unlimited PTO policy
AI First company
both Co-Founders are engineers at heart
and over 50% of the company is Engineering and Product
Family-Friendly environment
Regular team events and offsites
Unparalleled learning and professional development opportunities

Fulltime

Sr./Staff Data Scientist

Shape the future of trust in the age of AI. At Oscilar, we're building the most ...

Location

Salary:

Not provided

Oscilar

Expiration Date

Until further notice

Requirements

3+ years of experience in data science, machine learning, or a related field, with a focus on fraud prevention and/or anti-money laundering
Proficiency in Python
Fluency in cloud development (AWS, GCP, Azure, etc.) and MLOps is a plus
Strong knowledge of machine learning algorithms and statistical techniques, with a focus on their application in fraud detection
Experience working with large datasets using distributed systems like Apache Spark and Dask, handling data-related challenges such as data cleaning, data quality, and data transformation and feature engineering at scale
Excellent analytical and problem-solving skills, with the ability to derive actionable insights from complex data
Strong communication skills, with the ability to explain complex concepts and findings to both technical and non-technical audiences
Ability to work independently and collaboratively in a fast-paced, dynamic startup environment

Job Responsibility

Develop and implement advanced fraud detection models, leveraging machine learning and statistical techniques, to identify and prevent fraudulent activities across our platform
Collaborate with cross-functional teams, including engineering, product, and operations, to design and implement fraud detection systems and processes
Analyze large volumes of data to identify patterns, trends, and anomalies indicative of fraudulent behavior, and develop data-driven insights to improve fraud prevention strategies
Evaluate the performance of existing fraud detection models and systems, and continuously optimize and update them to adapt to changing fraud trends and tactics
Stay up-to-date with the latest trends and advancements in fraud detection, data science, and machine learning, and apply this knowledge to enhance our fraud prevention capabilities
Communicate complex data analysis and model performance results to both technical and non-technical stakeholders, driving data-driven decision-making across the organization
Ensure data privacy and security compliance in all aspects of fraud detection and data analysis

What we offer

Competitive salary and equity packages, including a 401k
Remote-first culture — work from anywhere
100% Employer covered comprehensive health, dental, and vision insurance with a top tier plan for you and your dependents (US)
Unlimited PTO policy
AI First company
both Co-Founders are engineers at heart
and over 50% of the company is Engineering and Product
Family-Friendly environment
Regular team events and offsites
Unparalleled learning and professional development opportunities

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

Fraud & AML Data Analyst

Shape the future of trust in the age of AI. At Oscilar, we're building the most ...

Location

Salary:

Not provided

Oscilar

Expiration Date

Until further notice

Requirements

4+ years of experience as a data analyst, data scientist or a related field, with a focus on fraud prevention and/or anti-money laundering
Proficiency in Python and SQL
Knowledge of machine learning algorithms and statistical techniques, with a focus on their application in fraud detection
Experience working with large datasets and handling data-related challenges such as data cleaning, data quality, and data transformation and feature engineering at scale
Excellent analytical and problem-solving skills, with the ability to derive actionable insights from complex data
Strong communication skills, with the ability to explain complex concepts and findings to both technical and non-technical audiences
Ability to work independently and collaboratively in a fast-paced, dynamic startup environment

Job Responsibility

Analyze large-scale transaction, account, and behavioral datasets to identify fraud, AML, and abuse patterns across: Onboarding (synthetic identity, fake accounts, mule risk), Account activity (ATO, session hijacking, social engineering), Payments (card-not-present fraud, ACH/wire fraud, crypto typologies)
Develop risk segmentation, cohorts, and KPIs (fraud rate, approval rate, loss rate, false positives)
Evaluate rule-based and ML-driven decision strategies and quantify performance trade-offs
Partner with customers to: Diagnose their fraud and AML pain points, Interpret model outputs, alerts, and decision logic, Design and refine risk strategies using our platform
Produce customer-facing analytics, dashboards, and readouts that translate data into actionable risk decisions
Act as a trusted analytics advisor for customers implementing or scaling fraud programs
Work closely with Product and Engineering to: Define data requirements and success metrics for new features, Provide feedback on model explainability, rule tooling, and case workflows, Identify gaps in data, signals, or product capabilities based on real customer usage
Support experimentation (A/B tests, challenger strategies, rule tuning)
Contribute to internal and external documentation, including: Fraud and AML best practices, Lifecycle risk frameworks, Playbooks for onboarding, ATO, and payment fraud
Help shape standardized analytics and reporting frameworks across customers

What we offer

Competitive salary and equity packages, including a 401k
Remote-first culture — work from anywhere
100% Employer covered health, dental, and vision insurance with a top tier plan for you and your dependents (US)
Unlimited PTO policy
AI First company
both Co-Founders are engineers at heart
and over 50% of the company is Engineering and Product
Family-Friendly environment
Regular team events and offsites
Unparalleled learning and professional development opportunities

Fulltime

Data Scientist - Fraud prevention

Subbyx

Location:
Italy , Milan

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
January 29, 2026

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