Data Automation (Python)

ERM is the world’s largest specialist sustainability consultancy, with over 50 years of experience helping organizations navigate complex environmental, social, and governance challenges. We bring together a global community of experts to deliver meaningful impact for our clients and the planet.

Our Consulting Delivery Hub (CDH) in India is a critical part of ERM’s global consulting model enabling scalable, high-quality delivery across regions and service lines. CDH teams work in close partnership with regional consultants to support global client projects, providing specialist expertise, driving consistency, and enhancing delivery efficiency across our most important programmes.

As part of the Consulting Delivery Hub, you will collaborate with colleagues worldwide, contribute to complex sustainability projects, and play a key role in shaping the future of global consulting delivery.

Why this role matters?

As a Data Scientist & Automation Specialist, you will support ERM's global consulting delivery by developing data-driven, AI-enabled, and automation solutions that improve decision-making, streamline workflows, and unlock value from structured and unstructured data. You will work within the Data Analytics & Visualization (DAV) service line,

partnering with regional project teams, technical specialists, and business stakeholders across global offices to deliver scalable analytics, machine learning, Generative AI, and automation solutions for environmental, sustainability, and business transformation projects. This role is critical to accelerating digital innovation, improving operational efficiency, enhancing data quality and insights, and enabling the scalable delivery of intelligent solutions across ERM's global portfolio.

What your impact is?

Develop and maintain Python-based automation solutions, reusable utilities, and data processing workflows.

Build, test, and deploy machine learning, NLP, OCR, and Generative AI solutions for business and environmental use cases.

Design and maintain ETL/ELT pipelines for structured and unstructured data from databases, APIs, documents, and cloud platforms.

Develop AI-powered assistants, RAG solutions, intelligent document processing workflows, and knowledge management systems.

Perform data cleansing, transformation, feature engineering, validation, and quality assurance activities.

Support implementation of cloud-based analytics solutions using Azure, AWS, Microsoft Fabric, and related technologies.

Utilize Git, Azure DevOps, and Agile methodologies to support collaborative software development and deployment.

What will you bring?

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, NLP, OCR, Computer Vision, or Generative AI technologies.

Experience developing ETL pipelines and working with APIs, databases, and cloud platforms.

Working knowledge of Azure, AWS, Microsoft Fabric, or similar cloud ecosystems.

Strong analytical, problem-solving, communication, and stakeholder engagement skills.

Preferred skills & competencies

Experience with Agentic AI, RAG architectures, LangChain, Copilot Studio, or LLM-based solutions.

Experience with PySpark, Airflow, MLflow, TensorFlow, PyTorch, or similar technologies.

Experience implementing OCR, document intelligence, and automated data extraction solutions.

Exposure to environmental, sustainability, ESG, GIS, or EHS datasets is considered advantageous.

Key responsibilities

Develop reusable analytics, data processing, AI, and automation frameworks to support scalable and efficient solution delivery across projects.

Collaborate with stakeholders to gather requirements and translate business challenges into data-driven, AI-enabled, and automation solutions.

Collaborate with project teams to identify automation opportunities and convert business requirements into scalable technical solutions.

Prepare technical documentation, testing records, user guides, and implementation artifacts.