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

Overview

Develop Python-driven data automation and analytics solutions for environmental projects.

Key Responsibilities

• etl pipelines
• airflow
• pyspark
• nlp
• ocr
• cloud deployment

Tasks

-Build and manage ETL pipelines using tools like Apache Airflow and PySpark. -Use Git for version control and collaborative development. -Apply natural language processing (NLP) and image processing techniques to extract insights from unstructured data (PDFs, DOCX, images). -Collaborate with project teams to identify data sources and ensure data quality. -Assist in OCR workflows and machine learning model development. -Support deployment of solutions on cloud platforms (Azure, AWS, GCP). -Develop and maintain Python scripts and automation workflows. -Contribute to scalable data engineering workflows and cloud-based analytics.

Requirements

• python
• azure
• aws
• gcp
• bachelor's
• nlp

What You Bring

-Proficiency in Python and familiarity with cloud services (Azure, AWS, GCP). -Strong communication and organizational skills. -1–3 years of experience in data science, automation, or data engineering. -Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field. -Ability to work independently and collaboratively in a fast-paced environment. -Experience with data wrangling, cleaning, and transformation. -Exposure to NLP, OCR, and machine learning concepts.

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About Erm

-Flourished through merging UK and US consultancies, building a truly global footprint. -Has carried out major environmental assessments for projects like High Speed 1, HS2, Keystone and Dakota Access pipelines. -Works in sectors from mining, energy and chemicals to manufacturing, pharma, power, renewables, finance and TMT. -Combines strategic advisory and technical delivery, using digital tools and proprietary methodologies. -Notably led environmental impact assessments for cross-border hydroelectric, rail and oil infrastructure.

Sector Specialisms