The Role
This is a full-time position as a Senior Data Scientist and this position may be located anywhere in the U.S. Design, develop and
deploy machine learning and statistical models that forecast customer cash flows, credit risk and other measures of business health.
Use experimentation and other statistical methods to test product, pricing and underwriting changes and to improve customer
experience on the platform. Explore and analyze large datasets to identify relevant signals, engineer features and uncover insights
that inform model and product design. Prototype and ship model driven features and data products that provide value to customers
and internal stakeholders. Research and evaluate advanced deep learning architectures and training techniques, including
transformer based and recurrent models, and implement innovations such as mixture of experts, semi supervised and generative
approaches to improve core underwriting algorithms. Monitor models in production, investigate performance issues and retrain or
update models as needed in collaboration with engineering, product and risk teams.
Qualifications
- Master of Science in Computer Science, Data Science, or a closely related discipline and 3 years as a Data Scientist or related
occupation.
- 3 years in the following:
- Building and optimizing deep learning models for forecasting, classification and ranking that predict key user, product or
business outcomes, including definition and improvement of model performance metrics such as accuracy, AUC, RMSE or
MAPE.
- Designing, training and evaluating deep learning models for sequence and time series data, including transformer based
architectures and recurrent neural networks, applied to forecasting or similar domains.
- Executing end to end machine learning projects, including data collection and preprocessing, feature engineering, model
development, deployment to production systems and ongoing performance monitoring.
- Machine learning, deep learning, optimization, statistics and probability theory, including the design and analysis of loss
functions, weight initialization schemes and neural network architectures under computational and data constraints.
- Statistical and causal inference methods, including probabilistic graphical models, Bayesian inference, difference in
differences or propensity score based methods, to estimate the impact of business or product interventions.
- Experimentation, including design, execution and analysis of A/B tests and offline and online experiments in production
environments.
- Large scale data processing and model training using modern machine learning frameworks such as PyTorch, TensorFlow,
JAX, scikit learn, MXNet or Spark, and cloud platforms such as AWS or GCP
Location
Position may work remotely from anywhere in the U.S. (HQ: San Francisco, CA
Compensation and Benefits
- We are a fully remote company and we believe in taking care of our employees. As a Pipe employee, you’ll receive:
- The best equipment to help you do your job.
- Flexible vacation and work hours. We believe in a healthy work-life balance (really!)
- Excellent health, dental, and vision insurance.
- Generous parental leave for anyone who is growing their family, regardless of gender.
- Great colleagues! We value a culture of authenticity, humility, and excellence. We want you to make a mark on our culture
Rate Of Pay
$270,000 to $290,000 per year. This salary range may be inclusive of several career levels at Pipe and will be narrowed during the
interview process based on a number of factors, including the candidate’s experience, qualifications, and location
