Senior Data Scientist

Insight Global
San Jose, CA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Software Code Optimization Python (Programming Language) Machine Learning Azure Machine Learning Feature Engineering Large Language Models Model Validation Machine Learning Operations Databricks

Job description

Overview Bill.com is seeking a Senior Data Scientist with strong Machine Learning Engineering experience to enhance and scale production ML models, pipelines, and platform capabilities. This individual will own machine learning solutions end-to-end, improve existing models through feature engineering and hyperparameter tuning, and contribute to the design of a new experimentation platform. Responsibilities

Contribute to the architecture and system design of a new experimentation platform. Contribute to BILL’s AI semantic layer to democratize advanced statistical capabilities to every employee in the enterprise Partner with Data Science, Engineering, Product, and GTM teams to operationalize ML solutions. Manage and optimize production machine learning models and data science pipelines. Build, deploy, and maintain scalable ML workflows and infrastructure. Improve inherited models through feature engineering, model evaluation, and hyperparameter tuning. Ensure reliability, monitoring, and performance of ML pipelines. Develop predictive models powering customer-facing experiences.

Requirements

7+ years of Data Science and/or Machine Learning Engineering experience. Strong Python development experience. Experience building and managing end-to-end ML pipelines in production environments. Hands-on experience with AWS SageMaker and Databricks. Expertise in feature engineering, model optimization, and ML lifecycle management. Strong system design and platform development experience. Familiarity with MLOps best practices and scalable machine learning architectures. Preferred

Experience building ML platforms or experimentation frameworks. Background in fintech, payments, risk, or fraud domains. Experience supporting high-scale production prediction systems. Experience with frontier AI technology Key Technologies: Python, AWS SageMaker, Databricks, Machine Learning, MLOps, Feature Engineering, Model Deployment, System Design, Predictive Modeling, AI, LLMs

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