Make a real difference with your engineering skills. At SheerID, we're building the future of data-driven marketing with our innovative Audience Data Platform, empowering businesses to understand and connect with consumers in powerful new ways. SheerID’s mission is to deliver a seamless verification experience for millions of users monthly, enabling access to exclusive offers while safeguarding data privacy.

As a Staff Data Scientist, you'll play a critical role in architecting, developing, and deploying cutting-edge SaaS solutions with a direct impact on our clients and SheerID's growth trajectory. Collaborate with a high-performing team to build high-quality, user-centric applications focusing on interoperability and scalability. You'll not only write code, but also mentor colleagues, conduct code reviews, and actively participate in knowledge-sharing to elevate the team's expertise.

We're seeking a passionate and experienced Java engineer with a strong foundation in data science and a commitment to crafting high-quality, user-friendly software. You thrive in collaborative environments, possess strong leadership qualities, and are eager to both share your knowledge and learn from others.

Role Specific Job Duties:

Lead the design and implementation of complex AI and machine learning solutions: Leverage your deep expertise to architect and develop high-performance, scalable models to detect and prevent fraud, with a focus on data-intensive applications.
Drive technical excellence and innovation: Champion best practices and explore emerging AI technologies, including advanced machine learning, deep learning, and graph analysis techniques, to enhance our fraud detection platform.
Mentor and guide fellow data scientists and engineers: Provide technical leadership, conduct comprehensive code and architectural reviews, and foster a culture of continuous learning and improvement.
Influence architectural decisions: Collaborate with engineering leadership and product managers to define and evolve the technical direction of our data platform and fraud strategies, clearly articulating model scaling and reliability trade-offs.
Solve the hairiest technical problems: Act as a technical escalation point, quickly identifying and evaluating potential solutions for the most challenging issues, from data quality to model performance.
Own the full data science lifecycle: From high-level design and development to model deployment, monitoring, and post-mortem analysis, take ownership of projects and drive them to successful completion.
Collaborate effectively: Work closely with product managers, data engineers, and other stakeholders to translate complex business requirements and research into robust, production-ready AI solutions.

Required Skills / Experience:

Bachelor’s degree in Computer Science, Software Engineering, Statistics, or a related quantitative field (equivalent experience considered).
10+ 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, 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.

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.