Posted 11 days ago
Senior Data Scientist - Fraud Detection
@ DataVisor
Toronto, ON · Vancouver, BC · Calgary, AB
Overview
DataVisor is hiring a Senior Data Scientist for its Fraud Detection team to build production machine learning fraud models and lead investigations into specific fraud attacks. Candidates need a Master's or PhD, 3+ years of applied fraud or risk experience, and strong Python and SQL skills.
Responsibilities:
- Lead end-to-end fraud detection model development
- Engineer features from large, noisy, imbalanced datasets
- Lead investigations into complex fraud cases
- Produce evidence-backed technical reports and trend reports
Requirements summary:
- Master's or PhD in a quantitative field
- 3+ years of fraud, cybersecurity or risk experience
- Strong Python and SQL skills
- Experience with production machine learning lifecycle
Tools & skills
Benefits mentioned
Source and dates
Employer career site / ATS feed · workable
- Employer posting date
- 2026-10-26
- First seen by our source
- 2026-10-11
- Source record updated
- 2026-10-27
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Data & analytics |
| Experience | 3+ years |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Master’s degree (required), Doctorate (required) |
| Fields of study | Computer Science, Statistics, Mathematics |
| Perks mentioned | Generous paid time off, Stock or equity |
Summary and details written by AI from the posting; the employer’s posting is the authority.
DataVisor
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
The most powerful AI fraud and AML detection platform trusted by the world's largest brands.
Full company description
DataVisor is the AI-native real-time decisioning engine for fraud and financial crime prevention. As AI transforms both fraud attacks and fraud defense, DataVisor helps financial institutions, payment providers, and digital businesses detect, investigate, and stop sophisticated and previously unseen threats in milliseconds across billions of transactions. Combining adaptive machine intelligence, consortium intelligence, and emerging agentic AI capabilities, DataVisor enables organizations to modernize fraud operations, improve customer experience, and stay ahead of rapidly evolving financial crime. DataVisor is trusted by leading financial institutions, payment innovators, Fortune 500 enterprises, and digital businesses worldwide.
- LinkedIn followers
- 66,918
- People associated on LinkedIn
- 164
- Reported office locations
- 967 N Shoreline Blvd, Mountain View, California 94043, US
- Business categories
- Cyber Security
- Fraud Detection
- Artificial Intelligence
- Software
- Internet
- Security
- Artificial Intelligence (AI)
- Big Data
- Machine Learning
- Other recorded names
- DataVisor
- Specialties
- Fraud Detection
- Fraud Prevention
- Artificial Intelligence
- Unsupervised Machine Learning
- Machine Learning
- AI Solutions
- Anti-Money Laundering
- Fraud Protection
- Agentic AI
- AI Fraud Detection
- and Real-time Decisioning
- Profile identifies a recruitment agency
- No
- Reported total investment
- 94,500,000
Currency and observation date were not supplied; this is not a current valuation or a funding round.
DataVisor is the AI-native real-time decisioning engine for fraud and financial crime prevention. As AI transforms both fraud attacks and fraud defense, DataVisor helps financial institutions, payment providers, and digital businesses detect, investigate, and stop sophisticated and previously unseen threats in milliseconds across billions of transactions. Combining adaptive machine intelligence, consortium…
| Field | Value |
|---|---|
| Industry | Software Development |
| Company size | 51-200 employees |
| Headquarters | Mountain View, California |
| Organization type | Privately Held |
| Year founded | 2013 |
| Specialties | Fraud DetectionFraud PreventionArtificial IntelligenceUnsupervised Machine LearningMachine LearningAI SolutionsAnti-Money LaunderingFraud ProtectionAgentic AIAI Fraud Detection |
| Open jobs on Jobsy | 18 |
| View page |
About DataVisor
DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!
Position Overview
We are looking for a Senior-Level Data Scientist to join our Fraud Detection team — someone equally comfortable building production ML models and getting hands-on with individual fraud cases. This is a dual-track role: you'll develop the machine learning systems that catch fraud at scale, and you'll personally lead investigations into how specific fraud attacks happened, reconstructing attacker behavior and turning case-level findings into trend reports and detection improvements. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real, visible impact in the fight against fraud.
Key Responsibilities
Machine Learning & Model Development
- End-to-End Model Development: Lead the full lifecycle of fraud detection features and models, from ideation and data exploration to prototyping, productionizing, and monitoring.
- Advanced Feature Engineering: Develop highly predictive features from complex, large-scale, multi-dimensional data, including user behavior, device intelligence, network graphs, and transaction records.
- Large-Scale Data Processing: Work with massive, noisy, and imbalanced datasets (billions of events) using tools like Spark, SQL, and our proprietary AI platform.
- Agentic AI & Automation: Leverage agentic AI to automate analytic pipelines and develop reusable skill tools that accelerate fraud investigation, feature generation, and reporting workflows.
Live Fraud Investigation & Reporting
- Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces. Reconstruct attacker sequences and hypothesize actor intent and tooling.
- Produce clear, evidence-backed technical reports and case studies for product, engineering, operations, legal, and executive stakeholders.
- Generate fraud trend reports for customers, synthesizing case-level findings and aggregate data into narratives customers can act on.
Requirements
Qualifications
Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
- 3+ years of applied experience in fraud detection, cybersecurity, or a related adversarial/high-velocity risk domain (fintech, consumer payments, banking, SaaS, marketplace risk, or security research).
- Solid understanding of both classic machine learning models (Logistic Regression, Gradient Boosting, etc.).
- Hands-on experience with the machine learning lifecycle in a production environment.
- Investigator mindset: demonstrated skill in pattern synthesis, hypothesis testing, and triaging signal from noise in ambiguous, adversarial cases — not just building and monitoring models.
- Strong programming skills in Python (must-have) and proficiency with SQL; experience with PySpark is a significant plus.
- Experience with large-scale data tools (Spark, Hadoop, etc.) and cloud platforms (AWS, GCP, Azure).
- Excellent communication skills — able to explain complex, ambiguous, or technical behavior clearly to both technical and non-technical audiences, including customers and executives.
- Professional proficiency in written and spoken English, with the ability to collaborate effectively in a global, cross-functional team.
Benefits
- Base salary range: $120,000–$150,000, commensurate with experience.
- PTO, Stock Options, Health Benefits
Journal
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