Data Scientist

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.

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.

• 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.

• Bachelors 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.

• 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

Lets 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: 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 and follow us on LinkedIn.

Required Experience:

IC