Staff Data Scientist, DocV

Socure; United States; On-site; USD 150,000 - 230,000; Full time

Job summary

United States Digital Space LLC seeks a Staff Data Scientist with deep expertise in computer vision and machine learning to provide technical leadership for document verification solutions. You will guide data scientists through the full model lifecycle from data strategy to production monitoring.

You will act as a domain expert, setting technical direction, mentoring teams, and collaborating with engineering, product, and customers to deliver effective modeling strategies.

Qualifications

• 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.
• Proven experience designing, deploying, and improving production ML systems at scale.
• Demonstrated technical leadership across multiple ML projects, including mentoring and guiding other experienced data scientists.
• Strong understanding of the full ML lifecycle, from data strategy and model development through deployment and production monitoring.
• Strong technical judgment and ability to navigate complex and ambiguous modeling problems.
• Excellent written and verbal communication skills, including the ability to influence technical, business, and customer stakeholders.
• Nice to Have Master’s or Ph.D. in Computer Science, Machine Learning, Computer Vision, or a related field.
• Experience with document verification, OCR, identity, fraud detection, or image forensics.
• Experience with transformer-based vision models, multimodal systems, foundation models, or LLMs.
• Experience working with enterprise customers or in regulated environments.

Responsibilities

• Oversee the end-to-end ML lifecycle, including data selection, model development, evaluation, deployment, monitoring, and continuous improvement.
• Guide and mentor data scientists through complex modeling and production challenges, helping teams make sound technical decisions and tradeoffs.
• Establish best practices and technical standards for model development, evaluation, and production readiness.
• Identify technical risks and opportunities across projects and drive solutions that improve model performance, scalability, and reliability.
• Partner with engineering, product, and customers to translate business and customer needs into effective modeling strategies.
• Communicate model behavior, performance, limitations, and technical decisions clearly to both technical and non-technical stakeholders.

Skills

Computer Vision

Machine Learning

Technical Leadership

Communication Skills

Education

Bachelor's degree in Computer Science or related field

Job description

Why the company?the company 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.

OverviewWe 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.

Responsibilities Serve as a domain expert in computer vision and machine learning, providing technical direction and guidance across document verification projects.

• Oversee the end-to-end ML lifecycle, including data selection, model development, evaluation, deployment, monitoring, and continuous improvement.

• Guide and mentor data scientists through complex modeling and production challenges, helping teams make sound technical decisions and tradeoffs.

• Establish best practices and technical standards for model development, evaluation, and production readiness.

• Identify technical risks and opportunities across projects and drive solutions that improve model performance, scalability, and reliability.

• Partner with engineering, product, and customers to translate business and customer needs into effective modeling strategies.

• Communicate model behavior, performance, limitations, and technical decisions clearly to both technical and non-technical stakeholders.

Requirements 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.

• Proven experience designing, deploying, and improving production ML systems at scale.

• Demonstrated technical leadership across multiple ML projects, including mentoring and guiding other experienced data scientists.

• Strong understanding of the full ML lifecycle, from data strategy and model development through deployment and production monitoring.

• Strong technical judgment and ability to navigate complex and ambiguous modeling problems.

• Excellent written and verbal communication skills, including the ability to influence technical, business, and customer stakeholders.

Nice to Have Master’s or Ph.D. in Computer Science, Machine Learning, Computer Vision, or a related field.

• Experience with document verification, OCR, identity, fraud detection, or image forensics.

• Experience with transformer-based vision models, multimodal systems, foundation models, or LLMs.

• Experience working with enterprise customers or in regulated environments.

the company 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 the company recruiting partner directly.

Follow Us!

YouTube | LinkedIn | X (Twitter) | Facebook