Sr. Data Scientist Job

Armstrong World Industries, Inc.; Rohrerstown (PA); On-site; USD 121,000 - 160,000; Full time

Job summary

Armstrong World Industries, Inc. is seeking a Senior Data Scientist to lead the development of advanced analytics and machine learning models that power key business decisions.

You will translate complex data insights into clear business value and partner with teams across data engineering, ML Ops, product, pricing, and finance. You will design, deploy scalable models and analytical tools, drive measurable outcomes, and communicate results to both technical and non-technical stakeholders.

Qualifications

• Strong proficiency in Python and ML/data libraries.
• Experience using AI platforms (Databricks).
• Expertise in statistical modeling, predictive analytics, and feature engineering.
• Experience with cloud platforms (AWS, Azure, or GCP) and MLOps practices.
• Proficiency in SQL, R, & Python and experience working with large-scale data environments.
• Strong understanding of model evaluation, AB testing.

Responsibilities

• Lead the design, development, and deployment of ML/AI models to solve complex business challenges.
• Partner with stakeholders to identify high-impact use cases and define measurable success criteria.
• Identify and build the right model to enable the business outcomes for each use case.
• Analyze large, complex datasets to uncover actionable insights and support data-driven decision-making.
• Collaborate with data engineers to ensure robust data pipelines and model integration into production systems.
• Build prototypes, conduct experiments, and iterate on model performance to drive continuous improvement.
• Connect LLMs to data sources to automatically summarize data, identify key metrics, and answer natural language questions.
• Leverage LLMs to generate summaries of analysis results and create visualizations.
• Apply LLM-powered NLP techniques for tasks such as text classification, sentiment analysis, and named entity recognition.
• Document processes and best practices in data science methodologies, coding standards, and model evaluation.
• Communicate results and recommendations clearly to both technical and non-technical audiences using data visualization and storytelling.
• Stay current with emerging tools, techniques, and trends in AI, ML, and data science.

Skills

Python

Databricks

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

AWS

Azure

GCP

SQL

R

Big data

AB testing

Tools

Databricks

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

SQL

Job description

Primary location:Lancaster,Pennsylvania
Relocation offered:No
Employment status:Full-Time
Travel:<10%
Non-compete:No

The estimated base salary range for this role is $121,000 to $160,000 per year.
Individual pay is based upon location, skills and expertise, experience and other relevant factors

What does it mean to work at Armstrong?

It means being immersed in a supportive culture that recognizes you as a key player in Armstrong's future. We are a large company with a local feel, where you will get to know and collaborate with leadership and your colleagues across the company.

By joining us, you'll have the opportunity to make the most of your potential. Alongside a competitive remuneration package, you will receive:

• A benefits package including: medical, dental, prescription drug, life insurance, 401k match, long-term disability coverage, vacation and sick time, product discount programs and many more.
• Personal development to grow your career with us based on your strengths and interests.
• A casual work environment where we have a recognition program for our team, and service awards. You will also be able to make the most of our fitness center and lunchtime cafe.
• A working culture that balances individual achievement with teamwork and collaboration. We draw on each other's strengths and allow for different work styles to build engagement and satisfaction to deliver results.

Armstrong is seeking a Senior Data Scientist to lead the development of advanced analytics, machine learning models, and data-driven solutions that power key business decisions. This role combines deep technical expertise with strategic thinking and strong communication skills to translate complex data insights into clear business value.

As a Senior Data Scientist, you will partner closely with cross-functional teams across data engineering, ML Ops engineering, product, pricing, finance, operations, and strategy to design, develop, and deploy scalable models and analytical tools that drive measurable outcomes.

What You'll Do

• Lead the design, development, and deployment of machine learning and AI models to solve complex business challenges.
• Partner with stakeholders to identify high-impact use cases and define measurable success criteria.
• Identify and build the right model to enable the business outcomes desired for each use case.
• Analyze large, complex datasets to uncover actionable insights and support data-driven decision-making.
• Collaborate with data engineers to ensure robust data pipelines and model integration into production systems.
• Build prototypes, conduct experiments, and iterate on model performance to drive continuous improvement.
• Connect LLMs to data sources to automatically summarize data, identify key metrics, and answer natural language questions.
• Leverage LLMs to generate summaries of analysis results and create visualizations.
• Apply LLM-powered NLP techniques for tasks such as text classification, sentiment analysis, and named entity recognition.
• Document processes and best practices in data science methodologies, coding standards, and model evaluation.
• Communicate results and recommendations clearly to both technical and non-technical audiences using data visualization and storytelling.
• Stay current with emerging tools, techniques, and trends in AI, ML, and data science.

What will make you successful

• Strong proficiency in Python and key ML/data libraries (Databricks, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, etc.).
• Experience using AI platforms (Databricks).
• Expertise in statistical modeling, predictive analytics, and feature engineering.
• Experience with cloud platforms (AWS, Azure, or GCP) and MLOps practices.
• Proficiency in SQL, R, & Python and experience working with large-scale data environments.
• Strong understanding of model evaluation, A/B testing, and