Intern - DocV & Device - Eng
Overview
Team: Document Verification (DocV) + Digital Intelligence (DI)
Location: Remote (U.S.)
Duration: 8 Weeks (June 15 – August 15, 2026)
You may collaborate with another intern working on a related project, sharing insights, approaches, and findings.
This internship offers a unique opportunity to work at the intersection of Document Verification (DocV), Digital Intelligence (DI), fraud detection, and behavioral analytics. The core focus is on exploring how behavioral and device signals—such as interaction timing, motion data, and environmental context—can be leveraged to better understand user sessions and strengthen fraud detection systems. The successful intern will evaluate, prototype, and demonstrate how these signals can improve decisioning accuracy, enhance system robustness, and be integrated into DocV and RiskOS workflows. You will not just observe; you will build, analyze, and deliver a portfolio-ready prototype that informs future detection and risk capabilities.
Project & Deliverables: What You’ll Work On
- Data Instrumentation & Collection - Instrument code to collect behavioral and device signals. Deliver a clean, structured dataset.
- Signal Analysis & Feature Engineering - Analyze data and engineer features. Deliver analysis showing signal impact.
- Detection Prototyping - Develop detection or scoring logic. Deliver a working proof-of-concept with metrics.
4. Integration & Documentation - Map integration points and document findings. Deliver technical documentation and presentation.
Technical Stack & Exposure
- Backend & Services: Go (Golang), Python, Java, APIs (REST / gRPC)
- Data Science & Analytics: Python (Pandas, NumPy, scikit-learn), SQL, Databricks
- Infrastructure & Tooling: Git, CI/CD, AWS, event-driven systems, observability tools
- Event Capture: JavaScript / TypeScript (basic instrumentation)
Candidate Qualifications
Required:
- Pursuing a degree in Computer Science, Engineering, Data Science, or similar
- Experience in Go, Python, or Java
- Familiarity with data analysis or ML concepts
- Understanding of APIs and backend systems
- Ability to work through ambiguity and iterate quickly
- Strong communication skills
Nice to Have:
- Exposure to fraud, identity, or security domains
- Experience with behavioral or event-based data
- Familiarity with SQL, Spark, or large-scale data tools
- Experience with dashboards or data visualization
Impact & Success
- Build a functional prototype using behavioral/device signals
- Demonstrate measurable improvements in detection or decisioning
- Identify high-value features for future integration
- Deliver a technical write-up and stakeholder presentation
Why This Role is Unique
- Work on real-world identity and fraud challenges
- Gain experience with production systems and data pipelines
- Receive mentorship from experienced engineers
- Deliver portfolio-ready work across engineering and data science