This role is responsible for building the tools, frameworks, and accelerators that enable the organization to scale AI, ML, and data science capabilities efficiently through automation and reusability
Job Summary
This role is responsible for building the tools, frameworks, and accelerators that enable the organization to scale AI, ML, and data science capabilities efficiently through automation and reusability.
By transforming manual, one-off analytics into automated, production-grade solutions that can be reused across multiple use cases, this leader dramatically increases the speed and consistency of analytics delivery.
US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits.
Matching Summary
This role is responsible for building the tools, frameworks, and accelerators that enable the organization to scale AI, ML, and data science capabilities efficiently through automation and reusability.
Salary
$145,600 - $270,400 per year; Bonus/Equity: performance-based cash incentive and annual equity awards; Benefits: health, life and disability benefits, 401(k) with company contribution and match, generous time off package
Skills & Requirements
Must-have
workflow automation solutions
CI/CD pipelines for data science
MLOps infrastructure design
reusable AI/ML components library
automated testing frameworks
workflow orchestration tools
Nice-to-have
creative problem-solver
strong systems thinking
building internal tools and platforms
pharmaceutical or regulated industries
analytics and software engineering best practices
Key Requirements
8+ years analytics engineering, data engineering, or software engineering
3+ years leading technical projects or small teams
Advanced degree in Computer Science, Data Science, Statistics, or related field; or Bachelor's degree with 8+ years relevant experience
Experience with CI/CD tools (GitHub Actions, Jenkins)
Knowledge of MLOps principles and tools (MLflow, Kubeflow, SageMaker)
Experience with testing frameworks and code quality tools