Senior Data Scientist - Document Verification

Socure Inc.
New York, NY, United States
26 days ago
Apply on www.indeed.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$191,000.0 - $230,000.0
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Amazon Web Services Data Analysis Computer Vision Fraud Prevention and Detection Image Quality Python (Programming Language) Machine Learning SQL Databases Usage Analysis Apache Spark Deep Learning
+6 more
Model Validation Information Technology Performance Monitor Build Tools GPT Databricks

Job description

We are seeking a highly technical Senior Data Scientist to drive machine learning innovation for Socure’s Document Verification (DocV) platform. This role combines model development, product analytics, model evaluation, and ML tooling to improve fraud detection, customer experience, and operational efficiency. You will partner closely with Product, Engineering, Fraud Operations, and Data Science to build production ML models, generate actionable insights, and develop scalable evaluation and automation frameworks., * Design, develop, and improve ML models for document verification, fraud detection, image quality assessment, biometric verification, and related use cases.

  • Research new features, modeling approaches, and fraud detection techniques to improve production performance.
  • Partner with Engineering to deploy, monitor, and continuously improve production models., * Analyze product performance, fraud trends, customer behavior, and emerging attack vectors.
  • Design and execute model evaluations using offline and production datasets, measuring precision, recall, FAR/FRR, and business impact.
  • Develop dashboards and KPIs to monitor model health, product performance, and operational metrics.

Tooling & Automation

  • Build tools and automation for model evaluation, performance monitoring, labeling workflows, and fraud investigations.
  • Develop self-service analytics and experimentation frameworks.
  • Improve analytics infrastructure supporting model development and monitoring.

Requirements

  • MS/PhD (or equivalent experience) in Computer Science, Statistics, Data Science, or a related field.
  • 5+ years of experience in machine learning, data science, fraud analytics, or product analytics.
  • Strong experience developing and evaluating production ML models.
  • Expert SQL and Python skills.
  • Experience with Databricks, Spark, AWS Sagemaker, or similar platforms.
  • Strong understanding of experimentation, statistical analysis, and ML evaluation.

Preferred

  • Experience with computer vision, deep learning, or transformer-based models.
  • Experience designing and analyzing A/B tests, online experiments, and statistical evaluations of product or machine learning performance.
  • Experience defining product KPIs and building dashboards to monitor product performance, customer behavior, and operational metrics.

About the company

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.indeed.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

40 sec

Generative pre-trained transformer models powering code completions

lgonta lgonta +1 · World Congress 2024

2:27 min

Managing traffic and tracking costs with Databricks Unity Catalog

Viktoria Semaan Viktoria Semaan · World Congress 2026 Europe

48 sec

Exploring alternative build tools and experimental web components

Sasha Shynkevich · LIVE

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

51 sec

Assessing GPT-4o performance for pull request feedback

Merrill Lutsky Merrill Lutsky · World Congress 2025

40 sec

Evaluating safety and data privacy in new software tools

Yewande Oyebo Yewande Oyebo · Europe 2026 Virtual

Videos

See all

Related articles

See all