Senior Data Scientist, DataVisor
LLMs for Fraud Detection
$140-170k
+ Stock Options
Office located in Mountain View, CA
Fraud & AML detection platform
Open for applications
Fraud & AML detection platform
101-200 employees
Open for applications
$140-170k
+ Stock Options
Office located in Mountain View, CA
101-200 employees
Company mission
To build and restore trust online.
Role
Who you are
- 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
What the job involves
- 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
- 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
- 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
Our take
As use of the internet rises, so too does the opportunity for fraud - with criminals exploiting the gaps that come with novel digital environments. DataVisor provides a fraud detection solution that leverages machine learning to identify threats. This helps to overcome the security gap caused by the speed at which today’s digital fraudsters evolve.
Traditional fraud solutions were not designed to handle digital data, and are ill-equipped to deal with quickly changing environments. By employing advanced ML, DataVisor can identify patterns which suggest fraudulent behaviour, allowing organisations to respond immediately and prevent losses before they happen.
Another problem has been that, in the name of security, systems might delay good customers from accessing services. With DataVisor, however, this becomes a non-issue, as the pattern of a non-malicious user can also be identified with speed.
DataVisor has seen considerable investment that has fuelled its continued expansion. It also boasts an impressive list of customers and partnerships. For example, a partnership with Equifax allowed it to extend it analytics and fraud detection capabilities. It has also launched the industry’s first unified, AI-powered SAR filing solution.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Dec 2022
$40m
LATE VC
Feb 2018
$40m
SERIES C
Total funding: $94.5m
Company benefits
- Stock Options
- Commuter Passes
- Paid Time Off
- Catered Lunch and Dinner
- Team and Company Outings
Company HQ
Mountain View, CA
Leadership
Yinglian Xie
(CEO & Co-founder)Extensive experience in security and AI. Previously a Senior Researcher at Microsoft Research.
Fang Yu
(CPO & Co-founder)Former Senior Researcher at Microsoft Research, with vast experience in big-data algorithms.
Salary benchmarks
We don't have enough data yet to provide salary benchmarks for this role.
Submit your salary to help other candidates with crowdsourced salary estimates.
Share this job
View 16 more jobs at DataVisor