Senior Data Scientist - Fraud AI & Data Pipelines

Why Socure?

Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.

We are seeking a highly analytical and impact-driven Senior Data Scientist to join our Data Science team  this role, you will work at the intersection of data, fraud risk, and identity verification, transforming raw, complex datasets into actionable insights that directly improve our products and decision‑making systems. You will own high‑impact projects end to end: designing scalable data pipelines, building and evaluating models, and leading analytical deep‑dives that shape how we use data to detect fraud and validate identity.

You will also leverage emerging approaches, including agentic AI and LLM‑powered systems, to automate data analysis, accelerate insight generation, and scale how we evaluate identity data and detect fraud patterns. This advanced individual‑contributor role (IC4 / Senior) requires deep technical expertise, strong business judgment, and alignment with Socure’s leadership competencies.

• Design, build, and maintain scalable data pipelines and workflows to support analytics, fraud detection, model development, and ongoing data monitoring (e.g., using Spark, Airflow, or similar distributed systems).
• Leverage and build agentic AI and LLM‑powered systems to automate data exploration, anomaly detection, vendor evaluation, and investigative workflows, increasing the speed and depth of insight generation.
• Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images, in support of fraud detection and identity verification use cases.
• Own data quality and integrity for critical datasets, implementing monitoring, validation checks, and anomaly detection to ensure reliable input to models and downstream decision systems.
• Take ownership of project outcomes from scoping through delivery, managing data quality, technical trade‑offs, and timelines; proactively escalating risks and working cross‑functionally to resolve challenges.
• Evaluate and integrate third‑party data vendors and external datasets, including designing experiments to assess data quality, coverage, lift, and long‑term value for Socure’s models and products.
• Collaborate closely with Product, Engineering, and Risk teams to define data requirements, shape roadmap priorities, and deliver insights that guide strategic decisions for fraud and identity products.
• Conduct in‑depth research to explore new data sources and develop novel algorithms and features that advance the state of the art in fraud detection, identity resolution, and risk scoring.
• Lead the end‑to‑end ML/analytics lifecycle for assigned projects: problem definition, data exploration, feature engineering, modeling, evaluation, deployment handoff, and post‑deployment monitoring where applicable.
• Present findings, trade‑offs, and recommendations to technical and executive stakeholders with clarity and influence, adapting communication for audiences ranging from engineers to non‑technical business leaders.
• Mentor and share knowledge with peers and junior data scientists, fostering a culture of experimentation, rapid iteration, and continuous learning aligned to Socure’s leadership competencies.
• Stay current with advancements in AI, machine learning, and data infrastructure (including LLMs and agentic frameworks), and apply innovative techniques to real‑world fraud and identity problems.
• Model Socure’s embedded leadership competencies in day‑to‑day work: continuous learning, effective communication, accountability, team development, decision making, and managing change.

• Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field; or equivalent professional experience.
• 5+ years of experience in data science, machine learning, or closely related roles, ideally in a high‑growth tech or fintech environment.
• Experience in…