Data Analyst - Ottawa, Canada - Canadian Wildlife Federation

Canadian Wildlife Federation

Verified Company

Ottawa, Canada

2 weeks ago

Posted by:

Sophia Lee

beBee Recruiter

Description

_Your Connection to Wildlife_:

As one of Canada's largest not for profit leaders in wildlife conservation, research, and advocacy, we are seeking to fill the following position _

Data Analyst

Who we are:

The Canadian Wildlife Federation (CWF) is a national not-for-profit charitable organization dedicated to ensuring an appreciation of our natural world and a lasting legacy of healthy wildlife and habitat.

By spreading knowledge of human impacts on the environment, developing and delivering educational programs, conducting research, promoting the sustainable use of natural resources, and advocating for effective wildlife policy and regulation, CWF strives for a future in which Canada's wildlife is conserved for generations to come.

Position Summary
CWF is looking to hire a Data Analyst based out of Head Office in Ottawa, ON.

Reporting to the Manager of Data Science and Web Development, the Data Analyst plays a crucial role as part of the IT/Operations Team in supporting fundraising initiatives and contributing to conservation science projects.

Education and Experience

Minimum Bachelor's degree in a quantitative or analytical field, such as Data Science, Statistics, or Computer Science.
2+ years of data analytics and data science experience.

Core Competencies
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Strong interpersonal skills: A strong ability to collaborate effectively with technical and non-technical staff, works well with teams across the organization and emphasizes a collaborative approach while working.
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Strong problem solver: Structured thinking and problem-solving skills and will persevere to meet business needs despite software constraints.
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Highly adaptable: Ability to learn new web and data platforms as CWF prepares to modernize legacy platforms to modern platforms.
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Conservation science: Strong knowledge of conservation science principles and datasets or the desire to learn and understand how data can conserve biodiversity.
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Effective prioritization skills: Ability to manage multiple projects and deadlines.

Technology Competencies

Data analytics, statistical modelling and data science techniques (e.g., machine learning, clustering, classification, predictive modelling, quantitative analysis)
Data visualization and data reporting for the purposes of decisionmaking and opportunity discovery
Data transformations and pipelines
Proficiency in programming languages such as Python or R
Experience working with fundraising data and familiarity with donor databases.
An understanding of software best practices and how these can be applied in the data domain
Blackbaud Raiser's Edge NXT and Luminate Online
SQL, Postgres SQL, MS SQL
Azure ecosystem, especially Microsoft Azure Data Factory
Microsoft PowerBI
Microsoft Excel
ETL software (e.g., Pentaho DI)
Experience with code version control (i.e., Git) is beneficial
Experience with at least one CRM such as MS Dynamics CRM, Raiser's Edge, Salesforce, etc.

Duties and Tasks

Data Analysis and Visualization:_
Utilize advanced statistical methods and data visualization techniques to analyze and interpret complex datasets.
Provide insights and recommendations to support fundraising strategies and optimize conservation science projects.
Fundraising Data Management:_
Analyze donor data to identify trends, patterns, and opportunities for donor engagement and retention.
Collaborate with the fundraising team to create reports and dashboards that facilitate datadriven decisionmaking.
Support fundraising campaigns by developing data products that drive the production of campaign materials.
Conservation Science Data Science:_
Work on data science projects related to conservation science, including analyzing biodiversity data, environmental trends, and other relevant datasets.
Implement predictive modeling and machine learning techniques to derive insights for conservation efforts.
Database Management and

Data Integration:
_

Manage and maintain databases relevant to fundraising and conservation science initiatives.
Ensure data accuracy, integrity, and security in compliance with organizational standards.
Build the infrastructure required for optimal extraction, transformation, and load of data from Blackbaud Raiser's Edge. Develop, manage and update pipelines for transformation, import and integration of external datasets into Blackbaud Raiser's Edge.
Maintain quality control over Raiser's Edge data entries and participation in the development of procedures to ensure quality control.
Reporting and Documentation:_
Generate regular reports and documentation summarizing key findings from data analyses.
Communicate results to diverse audiences, including fundraising teams, conservation scientists, and organizational leadership.
Develop internal documentation to ensure data is well documented and understood across the organization and workflows are reproducible.
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