Job description
A consumer fintech company using applied machine learning is hiring a Machine Learning Engineer to build and scale core product lines alongside product, engineering, and business leaders. Projects include fraud detection and prevention, risk underwriting for lending and advance programs, and predictive analytics for payout and repayment systems.
What you'll do
- Conduct data research and analysis on a large proprietary dataset
- Develop and validate models for growth, fraud mitigation, and risk control
- Iterate on models from real-world feedback
- Partner with data engineers and product managers to productionize models into high-scale data products
- Help build out the applied science and ML practice
Compensation
- $220,000 base
Location
On-site in Seattle, Washington.
Requirements
- Proven applied ML / applied science experience with a strong statistical inference background
- Required: a bachelor's or master's in Statistics, Mathematics, Physics, or Computer Science with an ML focus. Degrees in Business Analytics, Information Systems, or Data Science are not accepted for this role.
- Practical deep learning experience, particularly transformer-based models
- A track record of reading and implementing research papers
- Hands-on Python (PyTorch/TensorFlow) and SQL
- Modern ML techniques: model evaluation and validation, deep learning, time series, and tree-based models
Nice to have: FinTech domain knowledge.
Tech stack: Python, GCP, Go, BigQuery, MySQL.