Data Scientist Segment Lead

PPG Industries

1d•Hybrid

About The Position

As the Data Science Practice Lead within PPG's Digital Organization, this role is responsible for leading and shaping PPG's enterprise Data Science capability, with a primary emphasis on materials science, formulation, and process‑centric applied data science. The individual will bring deep hands-on expertise in materials and chemical data science—including formulation optimization, experimental design, structure–property modeling, and scale‑up analytics—while also providing technical leadership and architectural guidance for data science applications across manufacturing, supply chain, commercial, and customer-facing functions. This role bridges science, data, and digital product delivery, ensuring that advanced analytics and AI are best suited to the underlying physical, chemical, and operational realities of PPG's businesses. This role will sit at our headquarters in Pittsburgh, PA on a hybrid schedule. If not local - we will provide relocation benefits. Here at PPG we make it happen, and we seek candidates of the highest integrity and professionalism who share our values, with the commitment and drive to strive today to do better than yesterday – everyday. PPG: WE PROTECT AND BEAUTIFY THE WORLD™ Through leadership in innovation, sustainability and color, PPG helps customers in industrial, transportation, consumer products, and construction markets and aftermarkets to enhance more surfaces in more ways than does any other company. To learn more, visit www.ppg.com and follow @ PPG on Twitter. At PPG we use AI in the hiring process to make the process more efficient. AI tools do not make hiring decisions. You can learn more by going to https://careers.ppg.com/us/en/candidate-resources. PPG provides equal opportunity to all candidates and employees. We offer an opportunity to grow and develop your career in an environment that provides a fulfilling workplace for employees, creates an environment for continuous learning, and embraces the ideas and diversity of others. All qualified applicants will receive consideration for employment without regard to sex, pregnancy, race, color, creed, religion, national origin, age, disability status, marital status, veteran status, sexual orientation, gender identity or expression. If you need an adjustment due to a disability, please email [email protected]. PPG values your feedback on our recruiting process. We encourage you to visit Glassdoor.com and provide feedback on the process, so that we can do better today than yesterday. Benefits will be discussed with you by your recruiter during the hiring process. PPG pay ranges and benefits can vary by location which allows us to compensate employees competitively in different geographic markets. PPG considers several factors in making compensation decisions including, but not limited to, skill sets, experience and training, qualifications and education, licensure and certifications, and other organizational needs. Other incentives may apply. Our employee benefits programs are designed to support the health and well-being of our employees. Any insurance coverages and benefits will be in accordance with the terms and conditions of the applicable plans and associated governing plan documents. PPG is the world’s leading coatings company, serving more industries than any of our competitors. From automobiles and jetliners to wind turbine blades, and from ocean-going vessels and water tanks to family homes, our coatings and specialty materials help our customers protect, enhance and beautify valued assets. As part of our team, you’ll have access to world-class customers, industry experts, the best and brightest colleagues, and leading-edge technology.

Requirements

5+ years of experience in data science, applied analytics, or related fields, with a bachelor's degree or higher in data science, materials science, chemical engineering, statistics, physics, or a related discipline (or equivalent experience).
Deep, demonstrated expertise in materials‑ or chemistry‑adjacent applied data science, including experimental data analysis, DOE, formulation or process modeling, and optimization.
Proven experience leading and deploying advanced analytics and AI/ML solutions into production environments.
Strong foundation in statistical modeling, machine learning, and modern data science tooling.
Demonstrated ability to lead teams, mentor senior talent, and set technical direction.

Nice To Haves

Advanced degree (Master's or PhD) in Materials Science, Chemical Engineering, Chemistry, Applied Statistics, or related field.
Experience with hybrid physics‑based + ML models, Bayesian methods, or scientific computing.
Experience in applying data science across multiple enterprise functions
Strong executive communication skills and experience influencing senior leaders.

Responsibilities

Lead the PPG Data Science practice, setting technical standards, methodologies, and best practices for applied data science across the enterprise.
Serve as the senior technical authority for materials‑science‑driven data science, including formulation development, DOE‑based modeling, hybrid physics/ML approaches, and experimental data analytics.
Define and evolve domain‑appropriate modeling approaches (e.g., surrogate models, Bayesian optimization, multi‑objective optimization, structure–property relationships) aligned to scientific workflows in S&T and formulation teams.
Lead the design, development, and deployment of advanced AI/ML and statistical models that solve complex, real‑world problems rooted in chemistry, materials, and processes.
Guide teams from problem framing through deployment, ensuring models are scientifically sound, interpretable where required, and operationally robust.
Establish clear model performance, adoption, and value‑capture metrics tied to business and scientific outcomes.
Partner closely with S&T, formulation, manufacturing, quality, supply chain, commercial, and digital product teams to ensure data science solutions are embedded into real workflows.
Act as a technical translator across domains—helping non‑science functions understand how advanced data science applies to their problems and helping scientists leverage modern analytics effectively.
Ensure consistency and reuse of data science assets, patterns, and platforms across functions.
Define and influence data strategies and architectures that support scientific and operational analytics, including experimental data, lab systems, process data, and enterprise data platforms.
Ensure data quality, lineage, and integrity standards appropriate for scientific decision‑making and regulated environments.
Collaborate with data engineering and platform teams to ensure scalable, production-ready analytics infrastructure.
Establish best practices for model monitoring, validation, lifecycle management, and continuous improvement, particularly for models supporting scientific and operational decisions.
Promote responsible, transparent, and fit‑for-purpose use of AI/ML across domains.
Lead, mentor, and develop senior and mid‑level data scientists, with an emphasis on building domain‑aware data science talent.
Drive hiring, onboarding, and capability development for the Data Science practice, balancing deep domain expertise with modern ML skills.
Foster a culture of scientific rigor, experimentation, collaboration, and practical impact.
Communicate complex analytical concepts, results, and tradeoffs clearly to senior technical and business stakeholders.
Influence strategy by articulating where advanced data science is best suited to deliver differentiation and measurable value for PPG.