Applied Scientist

About the role

We are seeking an Applied Scientist to join our dynamic team. Your primary responsibility will be to develop and validate models that enable strategic business objectives, such as growth, fraud prevention, and risk management. You will work closely with product, engineering, and business leaders to ensure that your work directly impacts our users' financial well-being.

Responsibilities

• Perform data research and analysis using Grid's proprietary dataset and other relevant sources
• Develop and validate models that enable strategic business objectives, such as enabling growth, mitigating fraud, controlling risk, etc.
• Iterate on new and existing models based on feedback from team and real-world performance
• Collaborate with data engineers, product managers to help translate your work into production-grade, high scaled data products
• Present findings and communicate with members of the team with varying levels of technical depth
• Foster Data Science at Grid: Help build out our Applied Science and Machine Learning as a team and practice at Grid

Requirements

• Proven experience in Machine Learning and/or Applied Science, including a strong background in statistical inference, machine learning
• Bachelor's or Master's degree in Statistics, Mathematics, Physics, or Computer Science with a focus on machine learning
• Deep expertise in applied science and machine learning
• Research to implementation proficiency
• Robust technical skills: hands-on experience with Python (with libraries like PyTorch/TensorFlow) and SQL
• Autonomy and initiative: ability to work independently and take ownership of projects
• Curiosity and optimism: people who are constantly asking why the world around them works the way it does, and who have the will to change it
• Technical skills: proficiency in modern machine learning techniques, such as model evaluation and validation, deep learning, time series analysis, logistic regression, naive bayes, tree based models (i.e., random forest)
• Self-starter: confidence to prioritize work and deliver results on a tight cadence
• Demonstrated experience or understanding of the financial industry, especially in the context of building and scaling FinTech products

Qualifications

• Experience with AI tools for supporting parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information
• Final hiring decisions are made by humans

Benefits

Medical, Dental, Vision, 401K, Life Insurance

Pay

$120,000 - $140,000 per year