Senior Data Scientist

PPG•Pittsburgh, PA

10d•Hybrid

About The Position

PPG Digital Organization is accelerating enterprise-wide transformation by embedding advanced AI, machine learning, and data products across multiple domains, including formulation development (R&D), manufacturing, supply chain, commercial, and customer experience. We are seeking a Senior Data Scientist who is deeply technical, hands-on, and passionate about building high-quality machine learning models and production-ready solutions, to lead the delivery of high-impact AI/ML initiatives across the enterprise. You will work at the intersection of data science, applied AI, and software engineering, delivering solutions that are both scientifically rigorous and production-ready.

Requirements

Ph.D. in Data Science, Computer Science, Engineering, Chemistry, Physics, or related field.
5+ years of experience delivering AI/ML solutions in production environments
Strong expertise in: Machine learning and deep learning
Strong expertise in: Statistical modeling and optimization
Strong expertise in: Python and modern ML frameworks
Proven experience building scalable, production-grade ML systems
Experience working in Agile or product-oriented teams

Nice To Haves

Strong software engineering skills: System design and architecture
Strong software engineering skills: API development and microservices
Strong software engineering skills: Code quality, testing, and maintainability
Experience in: Generative AI (LLMs, prompt engineering, retrieval-augmented generation)
Experience in: Cloud-native AI platforms (Azure ML, AWS SageMaker, GCP Vertex AI)
Experience in: Distributed data systems (Spark, Databricks)
Experience leading or mentoring teams and driving cross-functional initiatives

Responsibilities

Devising and applying state-of-the-art machine learning, deep learning, and modern AI techniques (including Generative AI, LLMs and Multimodal AI) to solve business and scientific problems.
Evaluate AI/ML readiness and provide data acquisition recommendations to bridge gaps. Build production-grade machine learning solutions, not just prototypes.
Own the development of end-to-end AI/ML projects, including deployment into production environments, and monitoring for continuous improvement.
Design, develop, and maintain software components of internal data science platforms, enabling chemists, engineers, and business users to leverage AI/ML models through intuitive tools, APIs, and applications.
Work with modern data ecosystems (cloud platforms, distributed data systems, and real-time pipelines).
Communicate findings, assumptions, and model performance to both technical and non-technical stakeholders.
Work with global teams to translate innovative ideas into deployable digital products and services with quantifiable business impact.
Stay current on emerging technologies in AI/ML, software engineering, and applied data science.