# Senior Data Scientist - Fraud Data Infrastructure & Automation
**Company:** [Socure](https://hotfix.jobs/companies/socure)
**Location:** Remote
**Salary:** $170K-$200K
**Experience:** 5+ years
**Skills:** Python, SQL, PyTorch, TensorFlow, scikit-learn, Spark, Airflow, Databricks, LLMs, LangChain, LangGraph, Ray
**Posted:** 2026-04-28
> Senior Data Scientist builds scalable data pipelines, agentic AI/LLM systems, and ML models for fraud detection and identity verification using diverse data types. Owns end-to-end projects, ensures data quality, evaluates vendors, and collaborates cross-functionally. Requires 5+ years experience, Master's/PhD, Python/SQL/ML expertise.
## Job Description
## Responsibilities
- 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.
- 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.
- Take ownership of project outcomes from scoping through delivery, managing data quality, technical trade-offs, and timelines.
- Evaluate and integrate third-party data vendors and external datasets, including designing experiments to assess data quality, coverage, lift, and long-term value.
- Collaborate closely with Product, Engineering, and Risk teams to define data requirements, shape roadmap priorities, and deliver insights.
- Conduct in-depth research to explore new data sources and develop novel algorithms and features.
- 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.
- Present findings, trade-offs, and recommendations to technical and executive stakeholders.
- Mentor and share knowledge with peers and junior data scientists.

## Requirements
- **Education**: Master's or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, or related quantitative field (or equivalent experience).
- **Experience**: 5+ years in data science, machine learning, or related roles; experience in fraud prevention, risk modeling, or identity verification; working with large, messy datasets; diverse data modalities (tabular, text, point clouds, images).
- **Technical Skills**: Strong proficiency in **Python** and **SQL**; major ML libraries (**PyTorch**, **TensorFlow**, **scikit-learn**); machine learning algorithms and evaluation (AUC, lift, calibration); data pipelines in distributed environments (**Spark**, **Airflow**, **Databricks**); evaluating third-party data vendors.
- **Preferred**: Experience with **LLMs** and agentic AI frameworks (**LangChain**, **LangGraph**, **Ray**).
- Excellent communication skills; ability to lead technical workstreams and influence cross-functionally; commitment to continuous learning.
**Apply:** https://hotfix.jobs/jobs/senior-data-scientist-fraud-data-infrastructure-automation-at-socure-bc3be3bf-f8d0-455c-acc5-debccafb1e81
**Canonical:** https://hotfix.jobs/jobs/senior-data-scientist-fraud-data-infrastructure-automation-at-socure-bc3be3bf-f8d0-455c-acc5-debccafb1e81