data
Posted Apr 28Senior Data Scientist - Fraud Data Infrastructure & Automation
at Socure
United StatesHybrid
Responsibilities
- - 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.
- - 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.
Requirements
- 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.
- - 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.
- - 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.
- - 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.
- WHAT YOU BRING - 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 fraud prevention, risk modeling, or identity verification, including working with noisy, adversarial, or high-risk data environments. - Proven
- experience working with large, messy, real-world datasets to generate insights and drive measurable business impact (not limited to pure model development). -
- Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images, and selecting appropriate modeling approaches for each. - Strong proficiency in Python and SQL, with hands-on
- experience using major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn) for model development and evaluation. - Deep understanding of machine learning algorithms, model evaluation techniques (e.g., AUC, lift, calibration, stability), and data pipeline development for both batch and near-real-time use cases. -
- Experience building and maintaining data pipelines and workflows in distributed or large-scale environments (e.g., Spark, Airflow, Databricks, or similar technologies). - Demonstrated ability to evaluate and work with third-party data vendors or external datasets, including designing tests for data quality, coverage, stability, and incremental lift over existing signals. -
- Experience with LLMs and agentic AI frameworks/infrastructure (e.g., LangChain, LangGraph, Ray) is strongly preferred; ability to design or extend agentic workflows for analytics and data quality use cases is a plus.
- - Demonstrated ability to proactively deliver complex outcomes, lead technical workstreams, mentor others, and influence cross-functional decisions without formal authority.
- - Excellent written and verbal communication skills, with the ability to translate complex data problems and model behavior into actionable business insights for both technical and non-technical audiences.
Contact
- Follow Us! YouTube https://www.youtube.com/c/Socure | LinkedIn https://www.linkedin.com/company/socure/ | X (Twitter) https://x.com/socureme | Facebook https://www.facebook.com/socure/
Additional details
- 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 hire people who want that level of responsibility.
- People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision.
- If you want predictability or narrow scope, this won’t be your place.
- If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.
- ABOUT THE ROLE We are seeking a highly analytical and impact-driven Senior Data Scientist to join our Data Science Data team at Socure.
- In 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 decisioning 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.
- This is an advanced individual-contributor role (IC4 / Senior) that requires deep technical expertise, strong business judgment, and alignment with Socure’s leadership competencies, including continuous learning, effective communication, accountability, team development, decision making, and managing change.