Senior Data Scientist, DataVisor

Fraud Solutions

Salary not provided

+ Performance Bonus + Equity Options

SQL

Python

NumPy

Pandas

Scikit-Learn

Junior, Mid and Senior level

Remote from US

ML-powered fraud detection

Be an early applicant

ML-powered fraud detection

101-200 employees

B2BArtificial IntelligenceSecurityEnterpriseBig dataDeep TechAnalyticsMachine LearningSaaSAPICyber SecurityIdentityFraud

Be an early applicant

Salary not provided

+ Performance Bonus + Equity Options

SQL

Python

NumPy

Pandas

Scikit-Learn

Junior, Mid and Senior level

Remote from US

101-200 employees

B2BArtificial IntelligenceSecurityEnterpriseBig dataDeep TechAnalyticsMachine LearningSaaSAPICyber SecurityIdentityFraud

Company mission

To deliver the world’s most sophisticated AI-powered solutions to keep companies and their customers safe from fraud and abuse.

Job

Company

Role

Who you are

Experience: 1–5 years of hands-on experience in Data Science or Advanced Analytics
Technical Core: Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL
Statistical Rigor: Solid foundation in statistical modeling, feature selection, and performance evaluation (Precision/Recall, AUC, KS)

Desirable

Experience with graph theory or link analysis for detecting network-based fraud
Familiarity with unsupervised learning techniques or anomaly detection
Previous experience working in a high-growth SaaS or Fintech environment
Domain Knowledge: Familiarity with Fraud Detection, Credit Risk, or Trust & Safety, including knowledge of payment rails (FedNow, ACH, Wire) and typologies (Synthetic ID, ATO, Kiting)

What the job involves

We are seeking a hands-on Senior Data Scientist to serve as the "Architect of Efficacy" for our AI-Powered Fraud Solutions suite
In this role, you will move beyond simple analysis to build the mathematical core of our product
You will design pre-built detection strategies that provide immediate protection for new clients, solving the industry-wide "Cold Start" problem
Working at the intersection of research and product, you will collaborate closely with our Product, Strategy, Data Science, Delivery, and Engineering teams to translate complex fraud patterns into scalable, automated defenses
Develop Pre-Built Detection Models: Design, back-test, and optimize statistical baselines and machine learning strategies for our core solution modules, including Real-Time Payments (RTP), ACH, Wire, Check, and Application/Onboarding
Mine the Global Consortium: Analyze large-scale, cross-industry data within our global intelligence network to identify high-risk device fingerprints and patterns of organized fraud, transforming these insights into features that can be deployed across all clients
Architect "Cold Start" Logic: Create generalized scoring models that deliver immediate value to new clients, ensuring they are protected against known threats even before their historical data is fully integrated
Validate AI Agent Logic: Serve as the expert "Human-in-the-Loop" for our AI-driven strategy engine, rigorously testing and validating automated fraud detection logic to ensure safety, transparency, and low false positive rates
Cross-Functional R&D: Collaborate with Product, Strategy, Data Science, Delivery, and Engineering teams to explore and implement state-of-the-art machine learning and large language model (LLM) capabilities, providing the statistical rigor needed to turn experimental concepts into production-grade features

Our take

As the use of online shopping and banking continues to rise, so too does the opportunity for fraud, with criminals exploiting the gaps in defences that come with an increasingly novel digital environment. DataVisor provides the leading fraud detection solution that leverages machine learning to identify threats, to overcome the security gap caused by the speed at which today’s digital fraudsters evolve.

Traditional fraud solutions have not been designed to handle digital data, and they are especially ill-equipped to deal with quickly changing environments. By employing advanced ML, DataVisor can identify the patterns which allude to fraudulent behaviour, allowing organisations to respond immediately and prevent losses before they happen. Another problem with some systems has been that, in the name of security, they might delay ultimately good customers from accessing services. With DataVisor 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 will fuel its continued expansion across the globe - and has an impressive list of customers. The company has also made several partnerships that will act towards strengthening its product offering. For example, it is extending its analytics and fraud detection through partnership with Equifax, by gaining access to its rich consumer identity data.

Steph

Company Specialist at Welcome to the Jungle

Insights

Led by a woman

Glassdoor (4.4)

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)

Extensive experience in security and AI. Previously a Senior Researcher at Microsoft Research.

Fang Yu

(CPO)

Former Senior Researcher at Microsoft Research, with vast experience in big-data algorithms.

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