Data Analyst

Overview

Summary

: We are seeking an experienced and data-driven environmental specialist to join our Data Analytics department, focusing on the intersection of environmental science and the automotive industry. The ideal candidate will possess a deep understanding of environmental data analysis, impact assessment methodologies, source apportionment techniques, and atmospheric modeling (particularly WRF). This role involves leveraging data analytics to quantify the environmental footprint of automotive activities, developing data-informed mitigation strategies, interpret complex environmental datasets, and ensure compliance. You will play a key role in guiding our environmental strategy through rigorous data analysis within the automotive context

Responsibilities

:

− Apply advanced statistical and data analysis techniques to conduct comprehensive environmental impact assessments related to automotive vehicle lifecycles.

− Utilize source apportionment methodologies and data modeling to identify, quantify, and attribute contributions of automotive sources to air, water, and soil pollution.

− Process, analyze, and interpret large datasets from the Weather Research and Forecasting (WRF) model and other relevant atmospheric/environmental models to assess the dispersion and impact of automotive emissions.

− Analyze environmental and climate datasets to understand the impact of weather patterns and climate change on automotive-related environmental issues.

− Prepare detailed technical reports, data visualizations, dashboards, and presentations communicating complex environmental findings to internal stakeholders, regulatory bodies, and the scientific community.

− Design, manage, and analyze data from environmental monitoring programs.

− Provide expert guidance and mentorship on environmental data analysis techniques to subordinates and colleagues

Essential

:

− Minimum of 4 years of professional experience in environmental data analysis, modeling, consulting, research within the automotive sector

− Strong experience applying source apportionment techniques (e.g., receptor modeling, chemical mass balance) and interpreting the results

− Good understanding of air quality modelling, emission inventories, statistical analysis, and pollution control technologies relevant to vehicles

− Proficiency in data analysis programming languages (e.g., Python, R) and relevant libraries/tools (e.g., Pandas, NumPy, SciPy, WRF).

− Experience with database management and data visualization tools (e.g. Power Bl).

− Excellent analytical, problem-solving, and quantitative skills.

− Strong written and verbal communication skills, with the ability to present complex data findings clearly.

Desirable

:

− Experience with Life Cycle Assessment (LCA) methodologies and software.

− Advanced proficiency in Geographic Information Systems (GIS) for spatial environmental analysis.

− Experience working directly within the automotive industry or Tier 1 suppliers, particularly in a data-focused role.

− Knowledge of machine learning techniques applied to environmental data.

− Experience developing predictive environmental models.

− Project management experience, especially in data-intensive projects.