Staff Data Scientist
Omada Health- Full Time
- Senior (5 to 8 years)
Candidates should possess a Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline, and have at least 3 years of experience building and deploying machine learning models in a production environment. They should be proficient in supervised learning techniques and possess strong skills in software engineering practices, including test-driven development, code review, and refactoring. Experience with the PyData stack (NumPy, Scikit-learn, Pandas) is required, along with familiarity with tools like Spark, Kubernetes, Airflow, and MLFlow.
As a Staff Data Scientist, you will design, develop, and deploy machine learning models to solve practical problems and support the business and customers’ financial goals, collaborating with business leaders and technical experts. You will partner to develop new data sources, improve modeling methodologies, and apply models with sound risk management. Additionally, you will consider emerging tools like Chalk, BentoML, or DVC, and potentially develop in-house tools for training, interpreting, and deploying neural network architectures for time series classification tasks.
Provides transparent credit solutions and education
Mission Lane LLC offers credit cards designed to help individuals build or rebuild their credit, particularly those with limited credit history or financial setbacks. Their products feature no hidden fees, no security deposits, and instant approval decisions, making them more accessible than traditional credit cards. The company stands out by providing free access to credit scores and educational resources, helping clients improve their creditworthiness. Mission Lane's goal is to promote responsible credit use by rewarding good financial behavior with higher credit limits over time.