Senior Data Scientist

Required Skills & Experience

Required Qualifications

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.

Nice to Have Skills & Experience

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

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.