Data Scientist I

United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

E-commerce, Fraud Prevention, BiotechnologyIndustries

Requirements

Candidates must possess a degree in a STEM-related field or equivalent work experience, with at least 2 years of post-undergraduate professional experience. Required skills include project leadership, strong verbal and written communication, the ability to translate ambiguous problems into actionable analyses, and proficiency in influencing peers with data-driven storytelling. Candidates must be able to write and review Python code within a shared codebase, possess practical SQL knowledge, design experiments, collect data, and be familiar with the Linux command line. Bonus points are awarded for previous experience in fraud, payments, or e-commerce, data analysis in a distributed environment, and a passion for writing well-tested production-grade code. A Master's Degree or PhD is also considered a plus.

Responsibilities

The Data Scientist will contribute to building production machine learning models for fraud detection and improvement of the Signifyd Commerce Protection Platform. Responsibilities include researching real-time fraud patterns, deploying fraud-fighting rules and model threshold adjustments, and communicating complex ideas to diverse audiences, including executives. The role involves writing production and offline analytical code in Python, working with distributed data pipelines, and collaborating with engineering teams to enhance the machine-learning pipeline. The position also requires being directly responsible for the performance of enterprise merchants.

Skills

Machine Learning

Python

Data Pipelines

Fraud Detection

Risk Management

Statistical Analysis

Communication

Collaboration

Signifyd

Fraud protection for online retailers

About Signifyd

Signifyd specializes in fraud protection for online retailers, helping them detect and prevent fraudulent activities. The company provides a platform that uses machine learning and artificial intelligence to analyze transactions in real-time, identifying potential fraud. This service allows retailers to reduce chargebacks and approve more legitimate orders, ultimately increasing their revenue. Signifyd differentiates itself by offering a financial guarantee on approved transactions, meaning they will cover costs if a transaction they approve is later found to be fraudulent. This added security builds trust with clients. Operating globally, Signifyd ensures transparency with real-time data on system performance, allowing retailers to focus on their core business without the constant worry of fraud.

Palo Alto, CaliforniaHeadquarters

2011Year Founded

$399.8MTotal Funding

SERIES_ECompany Stage

Cybersecurity, AI & Machine LearningIndustries

501-1,000Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

Flexible Spending Account/Flexible Spending Account

Unlimited Paid Time Off

401(k) Company Match

Stock Options

Annual Performance Bonus

Paid Parental Leave

On-Demand Therapy for all employees & their dependents

Dedicated learning budget through Learnerbly

Company Social Events

Risks

Rise of 'friendly fraud' challenges Signifyd's financial guarantee model.

'Buy now, pay later' services introduce new fraud types that may evade current detection.

Flexible return policies in Europe could increase return fraud, straining existing strategies.

Differentiation

Signifyd offers a financial guarantee on approved transactions, covering potential fraud costs.

The company uses advanced AI and machine learning for real-time fraud detection.

Signifyd's global reach allows it to serve a diverse range of e-commerce clients.

Upsides

Partnership with Adobe Commerce enhances transaction intelligence and fraud protection capabilities.

$100 million Series D funding supports European market expansion and operational scaling.

Integration with Celerant shifts liability, attracting retailers seeking comprehensive fraud solutions.

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