Senior Climate Analyst

Role Overview: You will be responsible for identifying, sourcing, and conducting comprehensive reviews of datasets from multiple sources to support climate, environmental, nature/biodiversity, and regulatory datasets. You will also be conducting quality control reviews and validation of models, ensuring methodological rigor and accuracy in analytical outputs for research publications and client solutions. Additionally, you will be tasked with designing and implementing scalable data processing pipelines using Databricks and executing data science analytical workflows for processing large-scale datasets using established statistical modeling and machine learning frameworks. Automation of analytical pipelines for climate, environmental, nature, and regulatory datasets following established protocols will also be part of your responsibilities. Furthermore, you will support the presentation of research findings and recommendations to stakeholders through clear visualizations and text that effectively communicate complex data insights. Key Responsibilities: - Identify, source, and conduct comprehensive reviews of datasets from multiple sources - Conduct quality control reviews and validation of models - Design and implement scalable data processing pipelines using Databricks - Execute data science analytical workflows for processing large-scale datasets - Implement automation of analytical pipelines for climate, environmental, nature, and regulatory datasets - Support presentation of research findings and recommendations to stakeholders Qualifications Required: - 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 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 - Strong analytical and problem-solving skills with experience in data validation, quality control, and model testing methodologies - Excellent written and verbal communication skills with the ability to present complex technical findings to diverse stakeholder audiences Additional Details of the Company: Not present in the provided Job Description. Role Overview: You will be responsible for identifying, sourcing, and conducting comprehensive reviews of datasets from multiple sources to support climate, environmental, nature/biodiversity, and regulatory datasets. You will also be conducting quality control reviews and validation of models, ensuring methodological rigor and accuracy in analytical outputs for research publications and client solutions. Additionally, you will be tasked with designing and implementing scalable data processing pipelines using Databricks and executing data science analytical workflows for processing large-scale datasets using established statistical modeling and machine learning frameworks. Automation of analytical pipelines for climate, environmental, nature, and regulatory datasets following established protocols will also be part of your responsibilities. Furthermore, you will support the presentation of research findings and recommendations to stakeholders through clear visualizations and text that effectively communicate complex data insights. Key Responsibilities: - Identify, source, and conduct comprehensive reviews of datasets from multiple sources - Conduct quality control reviews and validation of models - Design and implement scalable data processing pipelines using Databricks - Execute data science analytical workflows for processing large-scale datasets - Implement automation of analytical pipelines for climate, environmental, nature, and regulatory datasets - Support presentation of research findings and recommendations to stakeholders Qualifications Required: - 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 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 - Strong analytical and problem-solving skills with experience in data validation, quality control, and model testing methodologies - Excellent written and verbal communication skills with the ability to present complex technical findings to diverse stakeholder audiences Additional Details of the Company: Not present in the provided Job Description.