Lead Data Scientist - Computer Vision

Job Summary
Founded in 2012, Socure is the leader in high-assurance digital identity verification technology.  Named to Forbes’ 2019 AI 50 list as one of America’s most promising AI companies and a recent winner of API World’s Best Data API, Socure’s technology applies artificial intelligence and machine learning techniques with trusted intelligence from email, address, phone, IP, social media, and the broader Internet to verify identities in real time. Socure’s customers include three of the top five U.S. banks, seven of the top 10 U.S. card issuers, as well as the majority of leading digital banks, lenders and insurers across the U.S. Socure is funded by some of the world's best investors and entrepreneurs including Scale Venture Partners, Commerce Ventures, Work-Bench, Santander InnoVentures, and Two Sigma Ventures.
In our mission to become the single, trusted source of identity verification and eliminate identity fraud from the internet, machine learning is at the core of the solutions we build. It’s how we innovate and how we offer the most accurate Identity Verification on the market.We are looking for a Lead Data Scientist - Computer Vision to join our US Data Science Computer Vision team.
The Computer vision team is responsible for building and maintaining computer vision solutions for document verification and fraud at Socure. If you enjoy building, optimizing, deploying, and maintaining  pipelines and infrastructure for machine learning/deep learning lifecycle from data collection/analytics to scalable deployment. Or if you enjoy building tools for others, and have a nose for automating data science work, we’d love to meet and talk about your experiences!
What You'll Be Doing:

• Develop machine learning solutions to solve challenging problems

• Design and implement robust and scalable systems and pipelines

• Build and maintain infrastructure in all aspects of the machine learning / deep learning lifecycle

• Demonstrate best practices in version control and continuous integration / delivery

• Own and drive initiatives from conception to completion and monitoring

• Collaborate with data scientists, engineers, product managers and other key stakeholders in a fast-paced cross-functional environment
   

What You’ll Bring:

• Advanced Degree in Computer Science or Related Field:

  • Master’s or Ph.D. in computer science, data science, artificial intelligence, or a related field with a focus on computer vision or machine learning.

• Proficiency in Programming Languages:

  • Strong programming skills in Python with extensive experience using libraries and frameworks such as PyTorch, TensorFlow, Keras, and OpenCV.

• 7-9 Years of experience in the following areas:

• Experience with Image and Video Analysis Techniques:

  • Proven track record in implementing and optimizing computer vision algorithms related to object detection, image segmentation, video analysis, and face recognition.

• Experience with Multimodal Model:

  • Demonstrated expertise in developing and integrating multimodal systems that leverage both visual and non-visual data (such as textual, layout, or tabular data) to enhance model performance and robustness in complex environments. This includes experience with fusion techniques for combining multiple types of data and applying these in practical, real-world applications.

• Machine Learning and Deep Learning Expertise:

  • Deep understanding of machine learning algorithms including deep learning architectures like CNNs, RNNs, and GANs, specifically applied to computer vision.

• Data Handling Skills:

  • Experience in handling, processing, and analyzing large datasets of images and videos, with a strong grasp of data augmentation and preprocessing techniques.

• Problem-Solving Skills:

  • Strong analytical skills with the ability to develop and deploy CV models that solve complex problems in a variety of application areas such as autonomous driving, augmented reality, or medical image analysis.

• Collaboration and Communication:

  • Excellent communication skills with the ability to work collaboratively in cross-functional teams to integrate computer vision systems into broader product offerings.

• Project Management Experience:

  • Demonstrated experience in managing projects from inception to completion, delivering actionable solutions in a timely manner.

• Industry Experience:

  • Prior work experience in industry applications of computer vision centric technology, such as in automotive, retail, healthcare, or security, is highly advantageous.