About the team
At Sift, our Data Science team works at the core of our Digital Trust & Safety platform, helping customers stop fraud, abuse, and account takeover while protecting great user experiences. We partner closely with engineering, product, and go-to-market teams to turn large-scale behavioral data into practical machine learning improvements and customer value.
We are a forward-thinking team that challenges the status quo, values open and constructive feedback, and cares deeply about learning, rigor, and impact. We take pride in our work, not ourselves, and we believe machine learning is a powerful way to help internet businesses grow safely.
Role
As a Data Scientist II at Sift, you will use data science and machine learning to improve fraud detection and customer outcomes. You will investigate fraud patterns, evaluate model behavior, prototype ideas, and work with engineering partners to translate research into production improvements. Your goal is to turn ambiguous customer and product problems into clear, data-driven recommendations that improve model quality, product capability, and business impact.
This is a strong fit for someone who enjoys both deep analysis and practical execution: someone who can dive into large datasets, frame the right questions, and communicate findings clearly to technical and non-technical partners alike.
What you’ll do
Analyze fraud patterns, customer behavior, and model outcomes to identify opportunities for product and model improvements.
Partner with engineering and product teams to define evaluation metrics, investigate gaps in current product behavior, and propose practical improvements that drive customer value.
Design and run experiments on features, modeling approaches, and datasets to validate ideas and improve model performance.
Evaluate model quality through dataset analysis, error analysis, calibration, and score distribution investigations.
Build repeatable analyses, prototypes, and internal tools that support research, diagnosis, and operational decision-making.
Communicate findings and recommendations clearly across data science, engineering, and business stakeholders.
What will make you a strong fit
Bachelor’s degree in Computer Science, Statistics, Mathematics, a related technical field, or equivalent practical experience.
2+ years of relevant industry experience in data science, machine learning, analytics, or a closely related field.
Strong foundation in machine learning and data science best practices, with experience applying them to real-world problems.
Experience working with large datasets using tools such as Python, Jupyter, Pandas, PySpark, scikit-learn, PyTorch, TensorFlow, or similar technologies.
Comfort performing both deep analysis and lightweight prototyping to test ideas quickly.
Strong problem-solving skills and the ability to work effectively in ambiguous spaces with competing priorities.
Clear communication and collaboration skills, with a team-first mindset.
Nice to have
Experience in fraud, risk, trust and safety, cybersecurity, or adjacent domains.
Familiarity with Java or another object-oriented programming language.
Experience partnering closely with software engineers to productionize analytical or machine learning improvements.
Please note: Final round interviews may be held in person
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.