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Mid-level popular ML role, metro location and common 3–6 years range increase applicant competition.
Core Python, ML, NLP, and ETL skills are highly transferable across industries.
Explicit 3–6 years plus specific ML, cloud, and automation tech requirements make filtering stringent.
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Develop and maintain Python-based automation solutions, reusable utilities, and data processing workflows for global sustainability consulting projects.
Build, test, and deploy machine learning, NLP, OCR, Generative AI solutions, and AI-powered assistants to improve decision-making and operational efficiency.
Design and maintain ETL/ELT pipelines and support cloud-based analytics implementation using Azure, AWS, Microsoft Fabric for structured and unstructured data.
Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Artificial Intelligence, or related discipline.
3–6 years of experience in Data Science, Automation, AI, Analytics, or Data Engineering.
Strong proficiency in Python, SQL, and data manipulation libraries such as Pandas and NumPy.
Experience with machine learning technologies including NLP, OCR, computer vision, or Generative AI, and working knowledge of Azure, AWS, or Microsoft Fabric cloud platforms.
Experienced in developing scalable, reusable analytics and automation frameworks for complex, multi-stakeholder environments.
Proficient in AI technologies including Agentic AI, RAG architectures, LangChain, and machine learning frameworks like TensorFlow or PyTorch.
Familiarity or experience with environmental, sustainability, ESG, GIS, or EHS datasets and associated data challenges.