Senior Data Scientist

Ukraine

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Digital Trust & Safety, Fraud Detection, CybersecurityIndustries

Requirements

Candidates should have over 5 years of experience as a data scientist in technology-focused teams, with proficiency in Python and SQL, and familiarity with big data tools like Spark and Snowflake. A deep understanding of machine learning techniques, end-to-end data science analysis, and excellent communication skills are essential. Bonus points include experience with AI/ML research, Trust & Safety domain knowledge, hands-on experience with deep learning models (LLMs, GenAI), and an advanced degree in a quantitative field.

Responsibilities

The Senior Data Scientist will design and execute hypothesis-driven experiments to evaluate product changes and quantify business impact. They will prototype cutting-edge machine learning and generative AI technologies for fraud detection, investigate adversarial behaviors, and develop robust detection strategies. Responsibilities also include collaborating with engineering, product, and other teams to build scalable solutions, and mentoring junior team members on best practices.

Skills

Machine Learning

Generative AI

Python

SQL

Spark

Snowflake

Data Science

Experimentation

Modeling

User Behavior Analytics

Adversarial Problem Solving

Sift

Real-time fraud detection and prevention platform

About Sift

Sift provides a platform focused on detecting and preventing online fraud in real-time, catering to clients in e-commerce, fintech, and digital marketplaces. The platform uses machine learning and artificial intelligence to analyze large datasets, allowing it to identify fraudulent activities effectively. One of its standout features is dynamic friction, which ensures that genuine users have a smooth experience while preventing fraudsters from accessing services. Sift's business model is subscription-based, with fees that depend on transaction volume and service level. Additionally, Sift offers services like chargeback management and dispute resolution, which add further value to its offerings. The company's goal is to enhance digital trust and safety for businesses by providing tools that help them make informed decisions and protect against fraud.

Bristol, United KingdomHeadquarters

2011Year Founded

$4.4MTotal Funding

SERIES_ACompany Stage

AI & Machine Learning, Financial ServicesIndustries

51-200Employees

Risks

Rise of app-enabled friendly fraud challenges Sift's mobile fraud detection capabilities.

Reliance on third-party delivery apps by QSRs introduces new fraud risks for Sift.

Complex payment processes may complicate Sift's integration and effectiveness in fraud prevention.

Differentiation

Sift offers a comprehensive platform for real-time online fraud detection and prevention.

The company uses machine learning and AI to analyze vast amounts of data effectively.

Sift's dynamic friction feature ensures seamless user experience while blocking fraudsters.

Upsides

Growing demand for AI-driven fraud detection in QSRs presents expansion opportunities for Sift.

Digital-first banks' need for effective authentication aligns with Sift's fraud prevention solutions.

Global trend towards secure payment systems supports Sift's mission for digital trust and safety.

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