Machine Learning Engineer

The role: We’re adding an Machine Learning Engineer to our team to help us build and scale our core product lines. You'll work closely with product, engineering and business leaders to make a difference with data. With access to multiple robust datasets and clear research objectives, you'll have a significant impact on Grid's progress as a business—as well as our users' happiness and success. Projects will include fraud detection, prevention and mitigation in novel arenas, such as risk underwriting for various lending/advance programs; predictive analytics to drive our payout and repayments systems; and more. The team We're focused on serving our users and building a robust product and business above all else. To this end, Grid's team members experience high levels autonomy and ownership, and as a company we value curiosity, learning and growth. As an Machine Learning Engineer, you'll have an opportunity not only to identify key leverage points for our data products, but also to set the standard for Grid's statistical inference and machine learning practice. The tech stack Our backend tech stack is based on Python, GCP, Go, protobufs, BigQuery and MySQL. We have built our platform from the ground up to optimize for clean data sources, and we have made numerous investments into data warehousing, streaming analytics infrastructure and offline data cleanliness. As a result, we think Grid is positioned for efficient and powerful applied science. What you'll doResearch & Analysis: Perform data research and analysis using Grid's proprietary dataset as well as other relevant sources Model Development: Develop and validate models that enable strategically relevant business objectives, such as enabling growth, mitigating fraud, controlling risk, etc. Deployment & Iteration: Iterate on new and existing models based on feedback from team and real-world performance Productionization : Collaborate with data engineers, product managers to help translate your work into production-grade, high scaled data products Present Findings : Present your findings and communicate with members of the team with varying levels of technical depth Foster DS @ Grid : Help build out our Applied Science and Machine Learning as a team and practice at Grid

What we're looking for: Applied Science Expertise:

• Proven experience in Machine Learning and/or Applied Science, including a strong background in statistical inference, machine learning.
• This is a requirement, a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a focus on machine learning is required. We are currently not accepting applicants with bachelor or master's degrees in Business Analytics, Information Systems, or Data Science.
• Deep Expertise in Applied Science & Machine Learning:
• Proven experience in applied machine learning, including a deep understanding of statistical inference and predictive modeling. Demonstrated practical experience withdeep learning techniques, particularly transformer-based models.
• Research to Implementation Proficiency:
• A strong track record ofreading, understanding, and implementing research papersin machine learning or related fields.

Technical Skills: Proficiency in the modern machine learning techniques, such as Model Evaluation and Validation, Deep Learning and Time Series Analysis, Logistic Regression, Naive Bayes, Tree based Models (i.e., Random Forest).Self Starter:

• Confidence to prioritize work and delivery demonstrable results on a tight cadence.
• Domain Knowledge:
• Demonstrated experience or understanding of the financial industry, especially in the context of building and scaling FinTech products.120000 - 140000 USD a year

Benefits: MedicalDentalVision 401KLife Insurance Salary Range $120,000 - $140,000 per year