Applied Scientist

About Grid

Grid is dedicated to reshaping the financial system to be fairer by offering tools that help individuals manage their financial futures. The Grid app provides access to cash, credit building, spending, and tax optimization, among other features. Our fast-growing team in Seattle is passionate about making a meaningful impact on millions of lives.

Role Overview

As an Applied Scientist at Grid, you will collaborate closely with product, engineering, and business teams to leverage data for substantial business impact and enhance user satisfaction. Your work will span projects like fraud detection in innovative lending contexts, predictive analytics for payments and repayments, and more, contributing directly to Grid's core product offerings.

Key Responsibilities

• Conduct rigorous data research and analysis utilizing Grid’s proprietary datasets along with other relevant sources.
• Design, develop, and validate models that support critical business goals such as growth enablement, fraud mitigation, and risk management.
• Iterate on model performance based on feedback and real-world results to continuously improve efficacy.
• Work with data engineers and product managers to implement and scale production-ready, high-performance data products.
• Effectively communicate research insights and technical details to diverse internal audiences.
• Contribute to the growth and establishment of Grid’s Applied Science and Machine Learning capabilities.

Required Qualifications

• Proven expertise in machine learning and applied science with a strong statistical inference foundation.
• Bachelor’s or master’s degree in Statistics, Mathematics, Physics, or Computer Science focused on machine learning (business analytics, information systems, or data science degrees are not accepted).
• Hands-on experience with advanced ML techniques, including deep learning and transformer-based models.
• Strong record of translating research publications into practical machine learning implementations.
• Proficiency in Python (including PyTorch/TensorFlow) and SQL.
• Independent worker with demonstrated initiative and ownership over projects.
• A natural curiosity about the mechanisms behind the world and a drive to enact change.
• Technical familiarity with model evaluation, time series analysis, logistic regression, Naive Bayes, and tree-based algorithms like random forests.
• Ability to manage priorities and deliver impactful results promptly.
• Relevant understanding or experience in the financial services industry, especially in building and scaling FinTech products.

Additional Information on Hiring

We utilize artificial intelligence tools to assist with parts of the hiring process such as resume review and application analysis. These tools augment but do not replace human decision-making; final hiring choices are made by our staff. For questions about data usage in recruitment, please contact us directly.

Benefits

• Medical insurance
• Dental coverage
• Vision plan
• 401(k) retirement benefits
• Life insurance

Salary

The annual compensation range for this position is $120,000 to $140,000.