Applied Analytics Engineer

Vulcan Materials Company • Birmingham, AL

72d

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.
• 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.
• 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.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Mining (except Oil and Gas)
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees