Data Scientist II - Big Data R&D, Identity Graph & KYC

About the Role

The Big Data R&D team is responsible for building the core identity graph and entity-resolution capabilities that power Socure’s KYC 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.

What You'll Do

• 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.
• Analyze large datasets to help develop and refine entity-resolution and identity-matching algorithms that drive Socure’s KYC and compliance solutions.
• Build and maintain components of data-processing pipelines (ETL, feature generation, normalization) using tools such as Spark/PySpark and AWS (e.g., EMR, S3).
• Support senior data scientists with feature engineering, data exploration, error analysis, and A/B test setup for new models and signals.
• Help evaluate new third‑party and internal data sources: profile data quality, design offline experiments, and summarize impact on coverage and model performance.
• Implement and maintain SQL and Python/R code for data extraction, transformation, and validation; contribute to code reviews and basic testing.
• Provide analytical support to compliance and regulatory product teams, including ad hoc investigations, simple dashboards, and data deep dives.
• Communicate findings in a clear, structured way to peers and cross‑functional partners (Product, Engineering, Client Analysis), focusing on key insights and trade‑offs.
• Work effectively in a fast‑paced, cross‑functional environment; demonstrate ownership of well-scoped tasks and follow through to completion.

What You Bring

• 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.
• Proficiency in at least one general-purpose programming language used in data science (Python, or Scala).
• Solid experience writing and optimizing SQL for large datasets; comfort working in data lake / warehouse environments.
• Hands‑on experience with Spark or PySpark and common ML libraries (e.g., scikit‑learn, XGBoost, TensorFlow/PyTorch a plus).
• Familiarity with UNIX environments and the AWS ecosystem (e.g., EMR, S3); Databricks experience is a plus.
• Working knowledge of supervised/unsupervised ML and basic statistics (similarity measures, clustering, evaluation metrics).
• Exposure to graph techniques or graph databases (Neo4j, AWS Neptune, GraphFrames) is a strong plus.
• Bonus: experience with Elasticsearch or DynamoDB; workflow tools such as Airflow for automating data pipelines.
• Ability to break down loosely defined problems, ask good clarifying questions, and iterate quickly with feedback.

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.…