Principal Data Scientist

Role Specific Job Duties: Architect Fraud Solutions: Partner with product & engineering to design and implement high-performance, scalable AI/ML models to detect and prevent fraud in data-intensive applications. Drive Innovation: Champion best practices and explore emerging technologies to enhance the fraud detection platform. Mentor and Lead: Provide technical leadership through architectural reviews and mentorship, fostering a culture of automation and continuous learning. Influence Strategy: Partner with product and engineering leadership to define the roadmap, balancing model scaling with reliability trade-offs. Solve Complex Challenges: Act as the technical escalation point for the "hairiest" problems, from data quality issues to model performance bottlenecks. Own the Lifecycle: Manage projects from design and development to deployment, monitoring, and post-mortem analysis. Collaborate Cross-Functionally: Translate complex business requirements and research into robust, production-ready AI solutions alongside engineers and product managers.. Required Skills / Experience: Bachelor’s degree in Computer Science, Software Engineering, Statistics, Mathematics, or a related quantitative field (equivalent experience considered). 20+ years of relevant experience in data science, with a strong focus on predictive fraud analytics and large-scale data applications. Proven ability to design, develop, and deploy scalable and maintainable 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), with extensive experience with relevant libraries and frameworks. Expertise in debugging complex data issues and model performance problems. Exceptional communication, interpersonal, and problem-solving skills, with a demonstrated ability to influence and lead across teams. Strong foundational knowledge of data architecture/data warehousing and a track record of execution. Preferred Experience: Expertise with Big Data, Data Science, or Stream Processing techniques. Experience applying advanced AI models, including computer vision and deep learning, to solve real-world problems. Experience with AWS, Kubernetes, VertexAI, Labelbox, and MLOps practices. Experience with SQL and NoSQL databases (MongoDB, Elasticsearch, etc.). Experience with graph analysis and network science for fraud detection. Experience with automated data processing pipelines and feature engineering at scale. SheerID is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We celebrate diversity and are committed to creating an inclusive environment for all candidates and employees. SheerID believes that diversity and inclusion is critical to our success as a company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. Please be aware that any communication related to this job posting will only come from email addresses ending in @sheerid.com. We strongly advise against engaging with any outreach from other sources, as they may be fraudulent. To ensure your safety, please note that we will never: Provide screening questions via email Extend a job offer without a formal interview process Request any personal information (such as Social Security numbers, banking details, etc.) through email or messaging platforms If you receive any unsolicited requests or suspect fraudulent activity, please report it immediately. Your safety and privacy are of the utmost importance to us. Thank you for your attention and caution.