Senior Data Scientist
New
P
PipeFinancial Technology
Remote, United StatesFull-TimeSenior
Salary270,000 - 290,000 USD per year
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Job Details
- Experience
- 3 years as a Data Scientist or related occupation
- Required Skills
- AWSGCPMachine LearningPyTorchData scienceSparkTensorflowDeep Learning
Requirements
- Master of Science in Computer Science, Data Science, or a closely related discipline.
- 3 years of professional experience as a Data Scientist or related occupation.
- 3 years of experience building and optimizing deep learning models for forecasting, classification and ranking.
- 3 years of experience designing, training and evaluating deep learning models for sequence and time series data, including transformer architectures and recurrent neural networks.
- 3 years of experience executing end-to-end machine learning projects, from data collection to deployment and monitoring.
- Deep understanding of machine learning, optimization, statistics and probability theory.
- Proficiency with statistical and causal inference methods, including Bayesian inference and propensity score based methods.
- Experience in the design, execution and analysis of A/B tests and production experiments.
- Experience with machine learning frameworks such as PyTorch, TensorFlow, JAX, scikit-learn, MXNet or Spark.
- Experience with cloud platforms such as AWS or GCP.
Responsibilities
- 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 to improve core underwriting algorithms.
- Monitor models in production, investigate performance issues and retrain or update models as needed.
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