Senior Data Scientist

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 Payment Protection 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.

What will you do:

In your first 3 months, you will:

• Get familiar with our systems, data, and fraud detection workflows.
• Design and run hypothesis-driven experiments and offline simulations to evaluate product changes.
• Begin prototyping machine learning and generative AI technologies to detect fraud and malicious behavior.
• Collaborate with cross-functional teams to understand workflows and identify opportunities for impact.

In your first 6 months, you will:

• Investigate adversarial behaviors and develop robust detection strategies for emerging threats.
• Deliver scalable, low-latency solutions in partnership with engineering and product teams.
• Mentor junior team members and contribute to best practices in experimentation, modeling, and research-to-production workflows.
• Drive insights from structured and sequential data, building models that directly influence product decisions.

In your first 9 months and beyond, you will:

• Lead end-to-end initiatives, from experimentation to production, delivering measurable business impact.
• Advance our use of cutting-edge ML and GenAI techniques, fine-tuning models for real-time prediction systems.
• Influence the broader product strategy by surfacing insights and shaping detection approaches for new and evolving threats.
• Serve as a trusted mentor and technical leader within the team, helping scale our experimentation and modeling capabilities.

What would make you a strong fit:

• 5+ years of experience as a Data Scientist or in a similar analytical/ML-focused role.
• Proven expertise in building and deploying models from structured or sequential data (ideally user activity logs).
• Strong technical skills: Python, SQL, and familiarity with big data tools (e.g., Spark, Snowflake).
• Solid understanding of ML techniques, data science best practices, and the end-to-end lifecycle from experimentation to production.
• Hands-on experience collaborating with engineering to productionize pipelines and deliver scalable insights.
• Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Proactive, self-starter mindset with strong prioritization skills and comfort with ambiguity.
• Willingness to adjust working hours occasionally for effective collaboration with West Coast colleagues.

Bonus points for:

• Background in Trust & Safety or fraud detection.
• Experience with deep learning, LLMs, and Generative AI (prompt engineering, fine-tuning).
• Contributions to AI/ML research or innovation (publications, patents, OSS, R&D).
• Experience with real-time, scalable prediction systems.
• Advanced degree (MS/PhD) in a quantitative field (AI, CS, Stats, Applied Math, etc.).

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:

• Introduction interview: a 45-minute session with a recruiter to discuss your background and the role.
• Technical screening interview: a 60-minute interview with the hiring manager to explore your fit for the position.
• Virtual onsite loop with the team: a comprehensive session comprising 3 interviews lasting approximately 3 hours, covering data science and ML foundations, coding abilities, and values-based conversations.

Visit us at sift.com and follow us on LinkedIn.