Data Scientist/Automation (Python, AcrPy, ArcEQuIS+ etc.)

• Design and implement scalable data pipelines and ETL processes using Apache Airflow, PySpark, and Databricks.
• Lead development of reusable, version-controlled codebases using Git and apply advanced NLP, OCR, and image processing techniques to extract insights from unstructured data.
• Architect and deploy solutions on Azure, AWS, and GCP using services like Azure Data Factory, S3, Lambda, and BigQuery.
• Collaborate with business domain experts to identify opportunities for data-driven solutions and document model designs, algorithm choices, and technical dependencies.

This role supports ERM's global initiatives by developing advanced data engineering and automation solutions that enable data-driven decision-making for environmental and resource management projects.

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, or a related field.
• 5–8 years of experience in data science, automation, or data engineering.
• Advanced proficiency in Python, Git, and cloud platforms (Azure, AWS, GCP).
• Strong experience with NLP, OCR, machine learning, and image processing, plus expertise in data pipeline architecture and cloud deployment.

No benefits, compensation, or perks information provided in the job description.

Environmental Resources Management (ERM) is a global consulting firm focused on environmental, health, safety, risk, and social consulting services, helping clients address sustainability challenges and manage environmental resources.