As a Staff Applied Scientist at OnePay, your key responsibilities will include designing and deploying machine learning and deep learning models, building AI agents for enhanced workflows, creating personalized recommendation systems, and optimizing search technology to improve user experiences. Your role will be central to shaping innovative solutions that elevate our financial products.

To qualify for the Staff Applied Scientist role at OnePay, you should have a strong technical background with a degree in Computer Science, Data Science, Applied Mathematics, or a related field. You'll need at least 8 years of experience in building and productionizing ML/AI models and expertise in developing AI agents or recommendation systems in a production environment.

At OnePay, collaboration is pivotal for the Staff Applied Scientist position. You'll work closely with product, engineering, and analytics teams, leveraging collective expertise to bring AI solutions from ideation to deployment, ensuring that our offerings meet customer needs and drive business growth together.

OnePay fosters a high-growth, mission-driven, inclusive culture where all team members are empowered to make an impact. As a Staff Applied Scientist, you’ll be surrounded by driven individuals who share the same passion for building innovative financial solutions and changing lives for the better.

OnePay offers a competitive salary, stock options, comprehensive health insurance, a hybrid work model, and various time-off programs, providing a supportive environment for balance and wellbeing. Starting from day one, you'll enjoy benefits that prioritize both personal and professional growth.

When answering, focus on the challenges you faced and the measurable impact of your project. Discuss the ML algorithms you used, your approach to deployment, collaboration with other teams, and how the project contributed to overall business goals.

Explain the key metrics you utilize based on the type of model (e.g., precision, recall, F1-score for classification; RMSE or R-squared for regression). Highlight the importance of validation techniques like cross-validation and your approach to tuning hyperparameters for optimal performance.

Focus on specific systems you've developed. Discuss the technology stack used, challenges encountered in tailoring recommendations, and how you measured user satisfaction or engagement due to these AI agents. Show your problem-solving mindset.

Discuss the resources you regularly consult, such as academic journals, online courses, workshops, and conferences. Emphasize your commitment to continuous learning and how you implement new findings into practical solutions within your work.

Explain how collaboration with product, engineering, and analytics leads to successfully implementing ML solutions. Highlight examples where team input shaped the final product, whether through insights or feedback during development processes.

Discuss specific techniques like grid search, random search, and Bayesian optimization. Talk about your experiences with performance tuning, adjusting model parameters, and balancing bias-variance trade-off to improve overall model accuracy.

Articulate your troubleshooting approach: verifying data quality, revisiting feature selection and engineering, considering model biases, or exploring more sophisticated algorithms. Emphasize your analytical mindset and methodical problem-solving skills.

Explain your methodology for feature selection, including techniques like correlation analysis, Recursive Feature Elimination (RFE), and utilizing domain knowledge to prioritize features that affect outcomes. Showcase your ability to connect features back to business goals.

Pick a specific challenge, detailing the context, your analysis process, the ML models employed, and the final outcomes or business impact achieved. Show your critical thinking and how you approach complex issues creatively.

Articulate your passion for using technology to improve financial services and how OnePay's mission aligns with your values. Mention specific aspects of the company culture and the innovative work they're doing that excite you about this opportunity.