Socure

<h2>Why Socure?</h2>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.<div><div></div></div><h3>Role Overview</h3>We are seeking a skilled and motivated Data Scientist II to join our Fraud &amp; Risk Data Science team. As an individual contributor, you will have autonomy in your day-to-day work and play an important role in driving functional productivity and project success. You will work hands-on with advanced deep learning models, collaborating with colleagues to deliver impactful solutions for fraud detection, risk management, and identity verification. This position provides the opportunity to contribute to diverse projects and collaborate within a supportive, high-performing team.<h3>Key Responsibilities</h3><ul><li>Design, develop, and implement advanced deep learning models, including transformers, CNNs, and LSTMs, to address complex fraud and risk challenges.</li><li>Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images.</li><li>Take ownership of assigned tasks, executing technical and functional activities to support project goals with minimal supervision.</li><li>Participate in all stages of the machine learning lifecycle: data exploration, feature engineering, model training, evaluation, and deployment.</li><li>Collaborate effectively across teams, sharing knowledge and learning from diverse perspectives to drive results.</li><li>Make routine technical decisions and contribute to functional objectives through productive and proactive engagement.</li><li>Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems.</li><li>Communicate results and insights clearly to both technical and non-technical audiences. </li></ul><h3>Qualifications</h3><ul><li>Bachelor’s degree with substantial related experience, Master’s degree with relevant experience, or equivalent work background in Computer Science, Statistics, Mathematics, Engineering, or a related field.</li><li>2-4 years of hands-on experience developing and deploying deep learning models (such as transformers, CNNs, and LSTMs).</li><li>Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images.</li><li>Proficiency in Python and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn).</li><li>Foundational understanding of machine learning algorithms, model evaluation techniques, and data pipeline development.</li><li>Experience with model deployment and monitoring in production environments (specific experience with real-time model inferencing is a plus)</li><li>Experience with LLMs and Agentic AI framework/infrastructure (e.g., LangChain/LangGraph/Ray) is a plus.</li><li>Strong problem-solving skills, with the ability to work independently on straightforward tasks and contribute effectively to project objectives.</li><li>Demonstrated ability to collaborate in a diverse, cross-functional team environment.</li><li>Excellent written and verbal communication skills.</li><li>Experience in fraud prevention, risk modeling, or identity verification is a plus. </li></ul><h3>Why Socure?</h3><ul><li>Join a mission-driven company at the forefront of identity verification and fraud prevention. </li><li>Work on impactful, challenging problems using cutting-edge technology. </li><li>Collaborate with talented colleagues in an inclusive, innovative culture. </li><li>Competitive compensation, equity, and benefits. </li><li>Opportunities for professional growth and skill development.</li></ul>Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us!<a target="_blank" rel="noopener noreferrer ugc" href="https://www.youtube.com/c/Socure">YouTube</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.linkedin.com/company/socure/">LinkedIn</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://x.com/socureme">X (Twitter)</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.facebook.com/socure/">Facebook</a>

Data Scientist II, Fraud & Risk

<h2>Why Socure?</h2>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.<div><div></div></div><h2>Overview</h2>We are seeking a Staff Data Scientist with deep expertise in computer vision and machine learning to provide technical leadership for our document verification solutions. This role is responsible for setting technical direction, guiding data scientists through complex challenges, and ensuring the quality of ML solutions across the full model lifecycle—from data strategy and model development to deployment, monitoring, and production usage.You will serve as a domain expert and trusted technical advisor, raising the technical bar across the team while partnering with engineering, product, and customers to deliver effective document verification solutions.<h2>Responsibilities</h2><ul><li>Serve as a domain expert in computer vision and machine learning, providing technical direction and guidance across document verification projects.</li><li>Oversee the end-to-end ML lifecycle, including data selection, model development, evaluation, deployment, monitoring, and continuous improvement.</li><li>Guide and mentor data scientists through complex modeling and production challenges, helping teams make sound technical decisions and tradeoffs.</li><li>Establish best practices and technical standards for model development, evaluation, and production readiness.</li><li>Identify technical risks and opportunities across projects and drive solutions that improve model performance, scalability, and reliability.</li><li>Partner with engineering, product, and customers to translate business and customer needs into effective modeling strategies.</li><li>Communicate model behavior, performance, limitations, and technical decisions clearly to both technical and non-technical stakeholders.</li></ul><h2>Requirements</h2><ul><li>Bachelor’s degree in Computer Science or a related field, or equivalent experience, with 10+ years or equivalent professional experience and deep expertise in computer vision and machine learning.</li><li>Proven experience designing, deploying, and improving production ML systems at scale.</li><li>Demonstrated technical leadership across multiple ML projects, including mentoring and guiding other experienced data scientists.</li><li>Strong understanding of the full ML lifecycle, from data strategy and model development through deployment and production monitoring.</li><li>Strong technical judgment and ability to navigate complex and ambiguous modeling problems.</li><li>Excellent written and verbal communication skills, including the ability to influence technical, business, and customer stakeholders.</li></ul><h2>Nice to Have</h2><ul><li>Master’s or Ph.D. in Computer Science, Machine Learning, Computer Vision, or a related field.</li><li>Experience with document verification, OCR, identity, fraud detection, or image forensics.</li><li>Experience with transformer-based vision models, multimodal systems, foundation models, or LLMs.</li><li>Experience working with enterprise customers or in regulated environments.</li></ul>Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us!<a target="_blank" rel="noopener noreferrer ugc" href="https://www.youtube.com/c/Socure">YouTube</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.linkedin.com/company/socure/">LinkedIn</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://x.com/socureme">X (Twitter)</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.facebook.com/socure/">Facebook</a>

Staff Data Scientist, DocV

<h2>Why Socure?</h2>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.<div><div></div></div>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 ROLEWe are looking for a Staff Data Scientist to join Socure's Watchlist Data Science team. Watchlist sits at the heart of global AML compliance — our platform screens hundreds of millions of entities in real time across sanctions lists, PEP databases, and adverse media sources for banks, fintechs, and payment companies worldwide.As a Staff Data Scientist, you will work on the hardest problems in entity matching and classification: scaling our patented real-time matching engine, building advanced Natural Language Processing (NLP) models for Named Entity Recognition (NER) and Information Extraction, and bringing next-generation research to production. This is a senior individual contributor role with broad technical ownership and direct impact on a product that helps the world's financial institutions manage sanctions and AML risk.WHAT YOU'LL DOData Quality &amp; Enrichment<ul><li>Improve the quality, coverage, and freshness of Watchlist's underlying data through next-generation ingestion pipelines.</li><li>Design and execute rigorous data quality analysis pipelines to identify anomalies, evaluate dataset health, and ensure high-fidelity inputs for downstream model training.</li><li>Apply NLP and AI to classify and enrich raw source data into normalized schemas — extracting structured entity attributes from unstructured sanctions, PEP, adverse media, and enforcement sources.</li><li>Expand multilingual capabilities to support global screening across Latin and non-Latin scripts.</li></ul>Entity Resolution<ul><li>Build and improve NLP systems that consolidate how watchlist identities are represented. Developing Information Extraction and Named Entity Recognition (NER) pipeline to deduplicate entities across lists and resolve aliases into canonical profiles..</li><li>Develop approaches to handle how entity profiles change over time as names, aliases, and sanctions status evolve.</li><li>Measure and benchmark entity resolution quality, driving continuous improvement in coverage and accuracy.</li></ul>Match Engine &amp; Risk Scoring<ul><li>Design and scale advanced NLP models and algorithms that perform real-time name matching and identity classification across diverse, multilingual unstructured data sources.</li><li>Build multi-signal risk scoring that combines name similarity, entity type, geography, list type, and other attributes into unified, calibrated risk scores.</li><li>Maintain and improve benchmarking frameworks, golden datasets, and regression tests that keep the match engine at the highest levels of recall and precision.</li></ul>Analytics, Tuning &amp; Evaluation<ul><li>Build models and analytics that help customers tune their screening thresholds to the right operating point for their risk appetite and entity mix.</li><li>Develop backtesting and counterfactual analysis capabilities so customers and internal teams can understand how model or threshold changes would affect screening outcomes.</li><li>Design evaluation frameworks for AI-powered autonomous decision systems — defining correct behavior, calibrating confidence thresholds, and monitoring for drift in production.</li></ul>AML Risk Detection<ul><li>As Watchlist expands into payment screening, build the mathematical analysis and feature engineering needed to detect AML risk patterns across transaction data and payment message fields.</li><li>Develop and maintain the AML taxonomy and risk signal library that underlies Watchlist's classification and detection capabilities.</li><li>Apply graph-based methods to surface indirect risk exposure — identifying entities connected to sanctions risk even when they are not directly listed.</li></ul> Research &amp; Technical Leadership<ul><li>Lead technical initiatives across Watchlist Data Science and shape the team's long-term approach to entity matching, enrichment, and AI.</li><li>Collaborate closely with Product and Engineering to translate research into production-grade systems at scale.</li><li>Stay current with advances in NLP, large language models, and entity resolution; prototype and deploy relevant techniques (e.g., advanced NER, LLM-based extraction) to AML use cases.</li><li>Mentor peers and contribute to a culture of technical rigor and continuous improvement.</li></ul>WHAT YOU BRING<ul><li>Master's or PhD in Computer Science, Computational Linguistics, Statistics, Applied Mathematics, or a related field; or equivalent professional experience.</li><li>7+ years of experience in data science or machine learning, with meaningful work in NLP, entity resolution, or information extraction.</li><li>Experience in AML, sanctions screening, adverse media, or financial crime detection is strongly preferred.</li><li>Hands-on experience building and deploying NLP pipelines for entity extraction, named entity recognition, and record linkage at production scale.</li><li>Familiarity with multilingual NLP and non-Latin script processing is a strong plus.</li><li>Experience with LLMs and agentic AI frameworks (e.g., LangChain/LangGraph) is a plus.</li><li>Strong proficiency in Python and major ML libraries (PyTorch, spaCy, HuggingFace Transformers).</li><li>Strong SQL proficiency and experience with large-scale data pipelines and production ML systems.</li><li>Excellent communication skills — able to translate model performance tradeoffs into compliance and business language for non-technical audiences.</li></ul>Note: We cannot provide Sponsorship at this time.You must be located in one of our talent hubs: New York, San Francisco, Seattle, or Miami.Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process — including interview or onboarding support — please reach out to your Socure recruiting partner directly.Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us!<a target="_blank" rel="noopener noreferrer ugc" href="https://www.youtube.com/c/Socure">YouTube</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.linkedin.com/company/socure/">LinkedIn</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://x.com/socureme">X (Twitter)</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.facebook.com/socure/">Facebook</a>

Staff Data Scientist, Watchlist

<h2>Why Socure?</h2>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.<div><div></div></div><h2>About the Role</h2>The Big Data R&amp;D team is responsible for building the core identity graph and entity-resolution capabilities that power Socure’s Deceased Monitoring and compliance products. In this role, you will help develop graph-based algorithms and data pipelines on massive PII datasets, support modelers with high-quality features, and evaluate new data sources that feed our identity and fraud products. You will work closely with senior data scientists and engineers while developing your skills in large-scale ML, distributed systems, and graph analytics.<h2>What You'll Do</h2><ul><li>Contribute to the design and implementation of machine learning, data mining, statistical, and graph-based algorithms to analyze very large datasets for identity verification and anomaly detection.</li><li>Analyze large datasets to help develop and refine entity-resolution and identity-matching algorithms that drive Socure’s Deceased Monitoring and compliance solutions.</li><li>Build and maintain components of data-processing pipelines (ETL, feature generation, normalization) using tools such as Spark/PySpark and AWS (e.g., EMR, S3).</li><li>Support senior data scientists with feature engineering, data exploration, error analysis, and A/B test setup for new models and signals.</li><li>Help evaluate new third‑party and internal data sources: profile data quality, design offline experiments, and summarize impact on coverage and model performance.</li><li>Implement and maintain SQL and Python/R code for data extraction, transformation, and validation; contribute to code reviews and basic testing.</li><li>Provide analytical support to compliance and regulatory product teams, including ad hoc investigations, simple dashboards, and data deep dives.</li><li>Communicate findings in a clear, structured way to peers and cross‑functional partners (Product, Engineering, Client Analysis), focusing on key insights and trade‑offs.</li><li>Work effectively in a fast‑paced, cross‑functional environment; demonstrate ownership of well-scoped tasks and follow through to completion.</li></ul><h2>What You Bring</h2><ul><li>Master’s degree with 2+ years of experience, or Ph.D. with 1+ years of experience in a data science or analytics role, or equivalent practical experience.</li><li>Proficiency in at least one general-purpose programming language used in data science (Python, or Scala).</li><li>Solid experience writing and optimizing SQL for large datasets; comfort working in data lake / warehouse environments.</li><li>Hands‑on experience with Spark or PySpark and common ML libraries (e.g., scikit‑learn, XGBoost, TensorFlow/PyTorch a plus).</li><li>Familiarity with UNIX environments and the AWS ecosystem (e.g., EMR, S3); Databricks experience is a plus.</li><li>Working knowledge of supervised/unsupervised ML and basic statistics (similarity measures, clustering, evaluation metrics).</li><li>Exposure to graph techniques or graph databases (Neo4j, AWS Neptune, GraphFrames) is a strong plus.</li><li>Bonus: experience with Elasticsearch or DynamoDB; workflow tools such as Airflow for automating data pipelines.</li><li>Ability to break down loosely defined problems, ask good clarifying questions, and iterate quickly with feedback.</li></ul><h3></h3>Please note that sponsorship is not available at this time; and that you must be located within 45 miles of a talent hub to be considered.Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us!<a target="_blank" rel="noopener noreferrer ugc" href="https://www.youtube.com/c/Socure">YouTube</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.linkedin.com/company/socure/">LinkedIn</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://x.com/socureme">X (Twitter)</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.facebook.com/socure/">Facebook</a>

Data Scientist II - Big Data R&D, Identity Graph & Deceased Monitoring

<h2>Why Socure?</h2>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.<div><div></div></div><h2>About the Role</h2>Socure is the leading provider of digital identity verification and fraud prevention solutions, leveraging AI and machine learning to power the most accurate identity trust decisions. Our mission is to eliminate identity fraud and ensure online trust across industries.We are seeking a Senior Data Scientist to join our Digital Intelligence team. In this role, you will drive the development of machine learning features and models that leverage device, network, and behavioral data to power fraud prevention and identity verification. You’ll work with rich, high-volume data from browser, mobile, and API traffic to surface meaningful insights and scalable risk signals. This is a great opportunity to own impactful projects, collaborate cross-functionally, and deepen your expertise in applied ML for device and behavioral intelligence.<h2>What You'll Do</h2><ul><li>Design and deploy advanced machine learning systems for device identification, anomaly detection, and fraud prevention—balancing precision, recall, and real-world adversarial dynamics.</li><li>Contribute to the development of scalable data pipelines and production ML workflows using structured and unstructured telemetry (e.g., browser, mobile, session data).</li><li>Investigate high-complexity signals (e.g., emulator use, spoofing, low-entropy fingerprints), applying advanced statistical methods and domain knowledge to detect fraud and abuse.</li><li>Translate ambiguous business problems into modeling approaches, using a combination of supervised, unsupervised, and heuristic techniques.</li><li>Partner with engineering, product, and risk teams to contribute to data architecture decisions, signal collection, and planning.</li><li>Drive experimental design, A/B testing frameworks, and robust validation techniques to ensure model generalizability and long-term trust.</li><li>Contribute to team standards for ML explainability, risk evaluation, and feature logging.</li><li>Document methodologies and communicate results effectively through dashboards, presentations, and reports for both technical and executive audiences.</li><li>Mentor junior data scientists and participate in cross-functional working groups.</li></ul><h2>What You Bring</h2><ul><li>Master’s degree (or equivalent practical experience) in Computer Science, Machine Learning, Statistics, or a related quantitative field.</li><li>6+ years of experience in data science or applied machine learning, including experience working in production environments.</li><li>Excellent SQL skills and extensive experience with large-scale databases and data modeling.</li><li>Proven track record of deploying and maintaining ML models in live systems, ideally involving streaming or near-real-time data.</li><li>Proficiency in Python and distributed computing tools (e.g., Spark, PySpark).</li><li>Hands-on experience with ML frameworks such as scikit-learn, XGBoost, TensorFlow, or similar.</li><li>Excellent communication skills—able to explain complex technical results to non-technical stakeholders and senior leadership.</li><li>Experience designing and interpreting experiments, working with real-world noisy datasets, and applying sound validation techniques to assess model robustness.</li><li>Demonstrated ability to break down ambiguous problems, apply analytical rigor, and uncover meaningful insights that influence product or risk strategies.</li><li>Strong judgment across data quality, model selection, and business impact tradeoffs.</li><li>Collaborative mindset and experience working cross-functionally with product, engineering, and analytics teams.</li></ul><h2>Preferred Qualifications</h2><ul><li>Background in fraud detection, behavioral biometrics, anomaly detection, or adversarial modeling.</li><li>Experience with high-cardinality feature engineering techniques (e.g., frequency/target encoding, embeddings).</li><li>Familiarity with privacy-preserving or robust ML techniques.</li><li>Knowledge of browser/mobile fingerprinting, VPN/proxy detection, or telemetry signal processing. </li></ul><h2>What You’ll Gain</h2><ul><li>Hands-on experience with real-world data science challenges in a high-impact industry.</li><li>A collaborative and inclusive work environment that fosters learning and growth.</li><li>Opportunities to grow into staff-level or technical leadership roles over time.</li></ul>Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us!<a target="_blank" rel="noopener noreferrer ugc" href="https://www.youtube.com/c/Socure">YouTube</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.linkedin.com/company/socure/">LinkedIn</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://x.com/socureme">X (Twitter)</a> | <a target="_blank" rel="noopener noreferrer ugc" href="https://www.facebook.com/socure/">Facebook</a>

Socure

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Data Scientist II, Fraud & Risk

Staff Data Scientist, DocV

Staff Data Scientist, Watchlist

Data Scientist II - Big Data R&D, Identity Graph & Deceased Monitoring

Senior Data Scientist - Digital Intelligence, Device Signals

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