Sift

Senior Data Scientist

Ukraine

Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Digital Trust & Safety, Fraud Detection, CybersecurityIndustries

Senior Data Scientist - Core Data Science

Employment Type: Full-Time Location Type: Remote Salary: Competitive Compensation (Includes financial rewards, annual 5% bonus, and stock options)

Position Overview

Sift is the leader in Digital Trust & Safety, helping businesses protect themselves and their customers from fraud and abuse. We combine machine learning, user behavior analytics, and cutting-edge AI technologies to power trust and reduce friction across the internet’s most valuable platforms.

We’re looking for a Senior Data Scientist to join our Core Data Science team and help shape the future of Trust & Safety using both machine learning and generative AI. You’ll prototype intelligent systems, surface insights from behavioral data, and partner closely with product and engineering to ship impactful solutions. As a senior member of the team, you’ll play a key role in shaping model architecture, solving adversarial problems, and mentoring other scientists.

Responsibilities

  • Design and run hypothesis-driven experiments and offline simulations to evaluate product changes and quantify business impact.
  • Evaluate and prototype cutting-edge machine learning and generative AI technologies to detect fraud and malicious behavior.
  • Investigate adversarial behaviors and develop robust detection strategies for emerging threats.
  • Collaborate cross-functionally with engineering, product, design, and customer teams to build scalable, low-latency, high-impact solutions.
  • Mentor junior team members and contribute to best practices in experimentation, modeling, and research-to-production workflows.

Requirements

  • 5+ years of experience working as a data scientist or in a similar role in technology-focused teams.
  • Experience developing models and insights from structured or sequential data, preferably in user activity log contexts.
  • Strong proficiency in Python and SQL, familiarity with big data tools (Spark, Snowflake, etc.).
  • Deep knowledge of machine learning techniques and data science best practices.
  • Experience with Data Science analysis end-to-end, working closely with Engineering to productionize pipelines, and surface insights in a scalable way.
  • Excellent communication skills with the ability to convey technical ideas to non-technical stakeholders.
  • A self-starter mindset with the ability to navigate ambiguity and prioritize effectively.

Bonus Points

  • Experience contributing to AI/ML research or innovation initiatives (publications, patents, open-source, or internal R&D).
  • Trust & Safety domain experience.
  • Hands-on experience with deep learning models, including LLMs, GenAI tools, prompt engineering, and fine-tuning.
  • Experience working with scalable, real-time prediction systems in production.
  • Advanced degree (MS or PhD) in Statistics, Artificial Intelligence, Computer Science, Applied Mathematics, Operations Research, or a related field.

Benefits and Perks

  • Competitive Compensation: Includes financial rewards, an annual 5% bonus, and stock options.
  • Health Insurance Stipend: Support for your medical and health-related needs.
  • Sports and Wellness Stipend: Encouraging a healthy and active lifestyle.
  • Work From Home Stipend: Support in creating a productive home office setup.
  • Education Reimbursement: books, education courses, and conferences to support your professional growth.
  • Mental Health Days: Additional paid day-offs to prioritize your well-being.
  • Language and Public Speaking Development: English courses and social activities within the company to enhance your communication skills.

Our Interview Process

  1. Introduction Interview: A 30-minute session with a recruiter to discuss your background and the role.
  2. Technical Screening Interview: A 60-minute interview with the hiring manager to explore your fit for the position.
  3. Virtual Onsite Loop with the Team: A comprehensive session comprising four interviews lasting approximately 4 hours, covering data science and ML background, coding abilities, cross-team collaboration & industry knowledge, and values-based conversations.

About Us

Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep in

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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