Water And Climate Data Scientist Jobs

Use project management tools in setting work objectives, detailing experimental scope, and timely execution of the projects towards sound technical solutions.

Expand capabilities through innovative internal and external research in areas related to pyrolysis, renewable fuels, gasification and others.

Effective communication skills and a willingness to seek out cross-functional technical expertise as required, with a proactive approach to problem-solving.

Mentor engineering and technical staff in applying fundamental chemical principles.

Investigate new and additional analytical tools for non-routine tests, near-real time and real time process chemistry.

Develop reactions kinetics, investigate reaction mechanisms and evaluate reactors hydrodynamics.

Three years of relevant experience in credit risk or portfolio management

Exceptional organization skills to prioritize, manage, and implement a variety of competing initiatives, on a concurrent or staggered basis

Manage collections analytics, performance monitoring and strategy evaluation routines

Strong collaboration and communication skills

Experience with statistical software packages such as R or SAS

Experience manipulating large and complex databases

Experience with Data Management standards relevant to ensuring data integrity;

Drafts communication materials and presentations for diverse stakeholder groups, including senior management, on EDC’s climate data initiatives.

Experience with the measurement of financed emissions aligned with PCAF and tracking progress against science-based targets (i.e. SBTI or PACTA);

Liaises with internal data engineering teams and external consultants to ensure alignment with EDC’s business requirements on climate data;

Experience of TCFD and relevant climate change reporting frameworks;

Experience with international organizations such as the IFC, WB, OECD and/or the UN;

Strong organizational and management skills with past experiences implementing best practices and processes

Translate product management, engineering, and business constraints and queries into tractable data science questions

Advanced Degree (Masters or PhD) or equivalent experience in Climate Science or related field required

2+ years of work or academic experience in risk modeling , extra plus if you have Climate Risk background

Experience working with machine learning

Experience deploying machine learning models in production environments

Strong organizational and management skills with past experiences implementing best practices and processes

Translate product management, engineering, and business constraints and queries into tractable data science questions

Advanced Degree (Masters or PhD) or equivalent experience in Climate Science or related field required

2+ years of work or academic experience in risk modeling , extra plus if you have Climate Risk background

Experience working with machine learning

Experience deploying machine learning models in production environments

Strong organizational and management skills with past experiences implementing best practices and processes

Translate product management, engineering, and business constraints and queries into tractable data science questions

Advanced Degree (Masters or PhD) or equivalent experience in Climate Science or related field required

2+ years of work or academic experience in risk modeling , extra plus if you have Climate Risk background

Experience working with machine learning

Experience deploying machine learning models in production environments

Strong organizational and management skills with past experiences implementing best practices and processes

Translate product management, engineering, and business constraints and queries into tractable data science questions

Advanced Degree (Masters or PhD) or equivalent experience in Climate Science or related field required

2+ years of work or academic experience in risk modeling , extra plus if you have Climate Risk background

Experience working with machine learning

Experience deploying machine learning models in production environments

Use project management tools in setting work objectives, detailing experimental scope, and timely execution of the projects towards sound technical solutions.

Expand capabilities through innovative internal and external research in areas related to pyrolysis, renewable fuels, gasification and others.

Effective communication skills and a willingness to seek out cross-functional technical expertise as required, with a proactive approach to problem-solving.

Mentor engineering and technical staff in applying fundamental chemical principles.

Investigate new and additional analytical tools for non-routine tests, near-real time and real time process chemistry.

Develop reactions kinetics, investigate reaction mechanisms and evaluate reactors hydrodynamics.

Overall Responsibilities And Key Accountabilities

0-3 years of practical experience in environmental monitoring;

Experience in either the oil and gas industry or mining is considered an asset; and

Perform tasks as requested efficiently and accurately, using standard methods and techniques;

Groundwater and surface water monitoring;

Tracking and reporting on field activity; and

Report preparation and writing skills are required, along with a solid understanding of MS Office suite and remote work software.

Geochemistry, hydrology, hydrogeology, water quality effects assessment, water resource management, aquatic biology

Knowledge and experience in the following areas is an asset:

Candidates will be considered for working from a remote office (within BC, AB, YT).

Regulatory approvals, mining, consulting or EA / permitting,

Social justice issues, Indigenous communities and environmental ethics.

Knowledge of data management and visualization techniques.

Excellent project management skills; enthusiastic about working on multiple fast paced projects at the same time

Work From Home - Flexible hours

Paid Time Off Benefits (4 weeks per year)

Design methodologies to enhance best practices in risk modelling and climate analytics by incorporating RTAI data infrastructure

Analysis of climate datasets to establish constraints, mechanistic connections, or sensitivity of target quantities to sources of variability (natural or forced)