ROLE OBJECTIVE:
In this role as an Economic Data Analyst/Scientist on the Data Development team, you will assist in building our core financial demographic products by processing, integrating, analysing, and visualizing a wide variety of large and small datasets. You will quickly understand and execute existing data processes while providing innovative feedback and ideas for improvement. We seek a detail-oriented, curious, and creative individual who can drive change and has a strong interest in economics and household finance. Your responsibilities will include building data products, analyzing financial and demographic data, and ensuring the accuracy and reliability of models and processes.
SPECIFIC RESPONSIBILITIES AND DUTIES:
To effectively fulfill the responsibilities of this position, the employee must be able to complete the following:
- Work within the Data Development team to produce high-quality, reliable financial data products.
- Learn and apply advanced concepts and methodologies related to data products and sources.
- Acquire, analyze, visualize, cleanse, impute, and transform large datasets from various sources.
- Ensure data products meet strict quality control standards at various stages of the product lifecycle.
- Analyze financial data outputs to ensure adherence to macroeconomic, microeconomic, and industry trends.
- Present findings and recommendations to stakeholders clearly and concisely.
- Stay updated with changes within the Canadian Economic landscape and advancements in data science and analytics.
- Skilled in Python for data processing, statistical analysis, and visualizations.
- Proficient in advanced SQL queries with a strong understanding of relational databases.
- Optimize data pipelines and workflows for efficiency and scalability.
- Strong problem-solving abilities, communication skills, and attention to detail.
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QUALIFICATIONS AND REQUIRED SKILLS:
- Education – Bachelor’s or Master’s Degree in a quantitative field such as Data Science, Quantitative Finance, Economics, Statistics, or a related Engineering degree.
Preferred Qualifications
- 1+ years of experience in building models and developing algorithms for data analysis, with a focus on macro and microeconomic data.
- Familiarity with financial databases and APIs.
- Understanding of Canadian geography and spatial analysis concepts.
- Experience working with Census and Financial Datasets (e.g., Statistics Canada, Canadian Revenue Agency, Equifax) is an asset.
- Highly skilled in Python and SQL
- Analytical Skills– Effectively researches and synthesizes complex or diverse information; uses intuition and experience to complement data and designs workflows and procedures. Innovative and capable of applying new and enhanced solutions to existing processes.
- Judgment– Displays willingness to make timely decisions, including appropriate people in the decision-making process and exhibits sound and accurate judgment; supports and explains reasoning for decisions
- Planning/Organizing– Prioritizes and plans work activities effectively. Ability to multitask.
Teamwork– Balances team and individual responsibilities; Exhibits objectivity and openness to others' views, giving and welcoming feedback. Puts the team's success above one's own interests and demonstrates the ability to build morale and group commitment to goals and objectives. Supports everyone's efforts to succeed.
- Innovation– Displays original thinking and creativity and meets challenges with resourcefulness. Generates suggestions for improving work. Presents ideas and information in a manner that gets others' agreement.
- Communication Skills– Able to clearly communicate ideas and expectations. Effectively listens for understanding and asks questions for clarification. Presents ideas effectively in both verbal and written form.
- Interpersonal Skills– Approachable and easy to talk to. Relates well to people across the organization. Able to effectively build rapport with others. Uses diplomacy and tact. Maintains composure and shows an ability to resolve conflicts and gain agreement.
