Your impact
When it comes to environmental consulting, we’re focused on advancing our clients’ environmental stewardship and sustainability initiatives.
Key Responsibilities In This Role:
- : You’ll work with subject matter experts in physical sciences and engineering to develop data-driven solutions for scientific and engineering challenges.
- Develop Scalable Data Workflows: You’ll build robust data pipelines, optimize workflows, and process complex datasets to uncover trends and actionable insights.
- Leverage Advanced Analytical Techniques: You’ll apply statistical, predictive modeling, and machine learning techniques to analyze large, structured, and unstructured datasets.
- Ensure High-Quality Data Solutions: You’ll design reproducible, efficient workflows with proper documentation and version control practices.
- Transform Data into Insights: We’ll lean on you to deliver clear, impactful visualizations and reports that make complex scientific data accessible to stakeholders.
- Facilitate Communication and Integration: You’ll be key in bridging the gap between domain expertise and data science, ensuring solutions align with project goals and real-world applications.
- : Solve scientific and engineering challenges using advanced data science to create practical, meaningful solutions.
- Collaborative Environment: Join a diverse team of domain experts, data scientists, and developers who value teamwork, creativity, and innovation.
- Growth Opportunities: Develop your skills and advance your career with opportunities for continuous learning and professional development.
- Innovative Work: Master cutting-edge tools and techniques to work on projects that shape the future of environmental and scientific solutions.
Here's what you'll need
- Bachelor’s degree in Physical Sciences (e.g., Geology, Chemistry, Biology, Physics) or Engineering (e.g., Environmental, Civil) or a closely related scientific field.
- Strong proficiency in R, with proven experience applying it to data analysis, statistical modeling, or workflow development.
- Minimum 5 years of experience as a Data Scientist, Data Analyst, or a similar role solving scientific or engineering challenges.
- Demonstrated ability to analyze and process large, complex datasets to extract meaningful patterns and insights.
- Experience developing and managing scalable data workflows and pipelines.
- Strong problem-solving skills with a solid foundation in statistics, linear algebra, and scientific analysis methods.
Ideally, you’ll also have
- Graduate degree in Physical Sciences, Engineering, Data Science, or a related quantitative field.
- Hands-on experience developing R-Shiny applications for data visualization and interactivity.
- Experience with geospatial analysis, GIS, and geodatabases.
- Familiarity with Docker for containerized application development and deployment.
- Proficiency in version control tools such as GitHub or Azure DevOps.
- Excellent communication and collaboration skills to work effectively with multidisciplinary teams.
- Experience with Power BI, Tableau, or other business intelligence tools.
- Knowledge of web development technologies, such as JavaScript, HTML5, or CSS.