Senior Data Scientist

SheerID

64d

About The Position

The role involves assisting with the design and implementation of complex AI and machine learning solutions, focusing on architecting and developing high-performance, scalable models to detect and prevent fraud. The position requires driving technical excellence and innovation by championing best practices and exploring emerging AI technologies, including advanced machine learning, deep learning, and graph analysis techniques. The candidate will mentor and guide fellow data scientists and engineers, providing technical leadership and fostering a culture of continuous learning and improvement. Additionally, the role includes influencing architectural decisions in collaboration with engineering leadership and product managers, solving complex technical problems, owning the full data science lifecycle, and collaborating effectively with various stakeholders to translate complex business requirements into robust, production-ready AI solutions.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Statistics, or a related quantitative field.
• 5+ years of relevant experience in data science with a focus on predictive fraud analytics.
• Proven ability to design, develop, and deploy scalable machine learning models in a production environment.
• Deep understanding of statistical methods, machine learning algorithms, and advanced data mining techniques.
• Proficiency in a statistical/general programming language (e.g., Python, R, Scala).
• Expertise in debugging complex data issues and model performance problems.
• Exceptional communication, interpersonal, and problem-solving skills.
• Strong foundational knowledge of data architecture/data warehousing.

Nice To Haves

• Expertise with Big Data, Data Science, or Stream Processing techniques.
• Experience applying advanced AI models, including computer vision and deep learning.
• Experience with GCP, Kubernetes, and DevOps practices.
• Experience with Swagger, REST, and Jenkins or similar build systems.
• Experience with SQL and NoSQL databases (MongoDB, CouchDB, Elasticsearch, etc.).
• Experience with graph analysis and network science for fraud detection.
• Experience with automated data processing pipelines and feature engineering at scale.

Responsibilities

• Assist with the design and implementation of complex AI and machine learning solutions.
• Drive technical excellence and innovation by exploring emerging AI technologies.
• Mentor and guide fellow data scientists and engineers.
• Influence architectural decisions and collaborate with engineering leadership and product managers.
• Act as a technical escalation point for challenging issues.
• Own the full data science lifecycle from design to deployment and monitoring.
• Collaborate effectively with product managers, data engineers, and other stakeholders.

What This Job Offers

• Education Level: Bachelor's degree
• Number of Employees: 101-250 employees