Senior Environment Analyst (with Python)

Crisil; Mumbai; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

Crisil is seeking a specialist in Climate Transition Risks and Opportunities to support climate-related datasets. The role involves identifying and validating datasets, implementing data processing pipelines, and presenting findings through clear visualizations.

The ideal candidate has 3-5 years of experience in data science and strong programming skills in Python, R, or SQL, along with a Bachelor's or Master's degree in a relevant field.

Qualifications

• 3-5 years of experience in data science, statistical modeling, or quantitative analysis.
• Hands-on experience with big data platforms and distributed computing environments.
• Excellent written and verbal communication skills for diverse stakeholder audiences.

Responsibilities

• Identify, source, and review datasets for climate and environmental datasets.
• Conduct quality control and validation of models for analytical outputs.
• Design and implement scalable data processing pipelines using Databricks.

Skills

Python

R

SQL

Data validation

Statistical modeling

Big data platforms

Analytical problem-solving

Education

Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Environmental Science, or related quantitative field

Tools

Databricks

Apache Spark

SimaPro

GaBi

open LCA

Job description

Job Description: Climate Transition Risks and Opportunities

Responsibilities and Impact

• Identify, source, and conduct comprehensive reviews of datasets from multiple sources to support climate, environmental, nature/biodiversity, and regulatory datasets
• Conduct comprehensive quality control reviews and validation of models, ensuring methodological rigor and accuracy in analytical outputs for research publications and client solutions
• Conduct data validation and model testing to support implementation of quantitative models. These models will include climate physical risk, climate transition risk and opportunity assessment, environmental impact/emissions analysis and environmental impact valuation
• Design and implement scalable data processing pipelines using Databricks
• Execute data science analytical workflows for processing large-scale datasets using established statistical modeling and machine learning frameworks
• Implement automation of analytical pipelines for climate, environmental, nature, and regulatory datasets following established protocols
• Support presentation of research findings and recommendations to stakeholders through clear visualizations and text that communicate complex data insights effectively

What We're Looking For

Basic Required Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Environmental Science, or related quantitative field
• 3-5 years of experience in data science, statistical modeling, or quantitative analysis with demonstrated proficiency in programming languages such as Python, R, or SQL
• Hands‑on experience with big data platforms and distributed computing environments such as Databricks, Apache Spark, or similar cloud‑based analytics platforms
• Proven experience developing and implementing models and statistical frameworks for large‑scale data processing and analysis
• Strong analytical and problem‑solving skills with experience in data validation, quality control, and model testing methodologies
• Excellent written and verbal communication skills with ability to present complex technical findings to diverse stakeholder audiences

Additional Desired Qualifications

• Experience with emissions factors development, validation, or application across various industry sectors and greenhouse gas scoping methodologies
• Knowledge of input‑output economic models for environmental impact assessment, including multi‑regional input‑output (MRIO) analysis or environmentally extended input‑output modeling
• Familiarity with natural capital valuation methodologies, ecosystem services assessment, or environmental accounting frameworks
• Understanding of life cycle analysis (LCA) principles, including cradle‑to‑grave assessment, impact categories, and LCA software tools such as SimaPro, GaBi, or open LCA.