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Applied Analytics EngineerVulcan Materials • United States
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Applied Analytics Engineer

Vulcan Materials
  • US
    United States
  • US
    United States
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About

Description
Build You
r Career. Build America's Future.
Vulcan Materials Company is the nation's largest producer of construction aggregates and a major producer of aggregates-based construction materials including asphalt and ready-mixed concrete. When you join Vulcan, it's more than starting an exciting career - you get to make a difference for millions of people every day across the country. When you join Vulcan, you join a dynamic culture in which career development is encouraged, excellence is rewarded and diversity is valued. No matter the role or the location across the country, every member of the Vulcan team lives through the Vulcan Way:
doing the right thing, the right way, at the right time. About The Job:
We are seeking a highly analytical professional with 3-5 years of demonstrable experience to join our team as an
Applied Analytics Engineer . The successful candidate will be responsible for the full-spectrum of technical work, with a primary emphasis on building, optimizing, and maintaining robust data pipelines that ingest, clean, and transform large, complex datasets for analytical readiness, and developing, rigorously testing, and deploying high-impact Machine Learning models into production systems for live use. The ideal candidate will translate complex business problems into measurable, scalable data solutions that drive strategic decision-making and business outcomes. What You'll Do:
Machine Learning & Statistical Analytics Design, build, and rigorously validate machine learning and statistical models (including regression, classification, clustering, and ensemble methods) for predictive and prescriptive analytics. Use deep analytical skills and data science knowledge to address complex, real-world business challenges and drive measurable impact. Analyze large amounts of information to discover critical trends and patterns. Apply the scientific method to design experiments, formulate hypotheses, and conduct rigorous testing. Apply expertise in natural language processing (NLP) and text mining techniques where applicable. Data Pipeline & Preparation Design, build, and maintain robust and scalable data pipelines to process, transform, and organize large, complex datasets from disparate sources. Identify, assess, and integrate valuable data sources, developing automated processes for continuous data collection and ingestion. Hands-on expertise in data management, programming, and processing large data volumes using technologies such as Python, SQL, and PySpark. Undertake meticulous preprocessing, cleansing, and transformation of large structured and unstructured datasets to ensure data quality, usability, and accuracy for modeling. Apply understanding of data management and data engineering principles to maintain scalable data architecture. Design dimensional data models using methodologies to ensure enterprise data consistency. Other Duties: Contribute to team efforts, including taking on new tasks as assigned by the supervisor. Assist with special projects as needed to support departmental goals. Handle cross-functional support duties, such as helping other departments with specific projects when required.
Qualifications
Skills You'll Need: 5 years of experience with statistical and programming languages for data analysis, specifically
Python (including PySpark, NumPy, Pandas, Scikit-learn)
and
SQL. 5 years of demonstrable experience in a data-focused role encompassing data exploration, data cleaning, and data visualization. Experience with cloud platforms (AWS, Azure, GCP) Practical experience with big data processing frameworks such as
Spark
or similar distributed computing environments. Extensive experience developing predictive
data models ,
quantitative analyses , and visualization of large data sources, including both structured and unstructured data. Experience leading or significantly contributing to the development of complex data solutions. Basic idea or hands on with
Tableau
or similar data visualization tools/stacks.
Good to Have:
Hands-on experience with
MLOps , Git Version Control, Unit/Integration/End-to-End Testing,
CI/CD , and release management processes. Hands-on experience with Snowflake, JIRA or ServiceNow. Design and implement data-grounded AI agents using large language models (LLMs) and specialized toolkits (e.g., LangChain, agent frameworks) to automate complex decision-making and data querying workflows. Familiarity with project management principles and best practices.
What You'll Like About Us:
Great Company Culture.
Our people share a competitive drive for excellence in an environment of trust, teamwork, open-mindedness and communication.
Safe.
Industry leader in health and safety standards. We are committed to creating a safe work environment and protecting all employees and customers.
Meaningful Work.
What sets up apart is the work we do impacts daily lives - and every employee contributes. Our aggregates produced are used to build roads, schools, hospitals, airports, and housing throughout the United States.
Health Benefits.
Medical, Dental, Vision programs, plus much more.
Rest and Relaxation.
Paid vacation, personal floating days, and paid holidays.
Prepare for the Future.
401(k) with company match and contribution.
Training and Development. We see our development programs and helping our employees meet their goals as a key part of our business. Vulcan Materials Company is committed to employing a diverse workforce. You will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability. You also have the right to be free from discrimination for medical needs arising from pregnancy, childbirth, or related medical conditions.
Job: Applications & Software Primary Location: Texas-Irving Organization: GM - CORPORATE Schedule: Full-time Job Posting: Jun 8, 2026, 1:23:09 PM
  • United States

Languages

  • English
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