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Data Analyst II

3 hours ago

Winnipeg, Manitoba, Canada Access Credit Union Full time
Grow your career with one of Manitoba's Top Employers since 2014.

At Access Credit Union, we support a professional and innovative work environment with a corporate culture that uniquely embraces empowerment, accountability, and trust. We recognize and value each employee's contributions to our success, which is why we offer competitive compensation, 100% company paid health benefits, employer-matched pension plan, continuing education, and career advancement opportunities within our credit union.

At Access Credit Union, our values are straightforward:

  • Do good
  • Be better
  • Own it
  • Move forward

Data Analyst II has the experience creating business value through the development and deployment of advanced analytics solutions to provide business insights that enable strategic decision making and market growth. A Data Analyst has intermediate theoretical and practical working knowledge of AI such as LLM, ML, RPA, Generative AI, Agentic AI, Deep research, prompt engineering, statistical machine learning topics, concepts & methodologies. You would have experience using artificial intelligence (AI) techniques, like machine learning algorithms, to extract insights from large datasets, focusing on data cleaning, processing, and analysis to identify patterns and trends, often with the goal of developing predictive models and creating informed business decisions.

Key Responsibilities & Accountabilities

Advanced Data Analysis

  • Conducting in-depth analysis to identify trends, patterns, and insights from large datasets. This helps in making data-driven decisions and uncovering hidden opportunities.
  • Analyzing large and complex data sets to extract meaningful insights.
  • Developing, implementing, and maintaining data models and algorithms.
  • Presenting findings and insights to stakeholders through visualizations and reports.

Data Modeling

  • Developing and maintaining data models to predict future trends and behaviors. This includes creating statistical models and machine learning algorithms to solve business problems.
  • Ensuring regulatory compliance, security and privacy are maintained at all times.

Data Preparation

  • Performing data cleaning, preprocessing, and feature engineering to ensure data quality and readiness for analysis. This step is crucial for accurate and reliable results.

Collaboration

  • Working closely with cross-functional teams, such as marketing, finance, and operations, to understand their data needs and provide actionable insights and translate them into data-driven solutions.
  • Work alongside the Data Scientist's and application developers to assist in training and analyzing data, creating technical documentation.
  • Maintain an in-depth knowledge of the credit union industry, lines of business and industry trends
  • Collaborating with cross-functional teams

Reporting and Visualization

  • Creating detailed reports and interactive dashboards to present findings to stakeholders. This involves using tools like Power BI, or similar to make data insights accessible and understandable.

Process Improvement

  • Identifying inefficiencies and suggesting improvements in data collection, storage, and analysis processes. This helps in optimizing workflows and enhancing data management practices.

Mentoring

  • Assisting junior data analysts by providing guidance and support on various projects. This includes helping them develop their skills and ensuring the quality of their work.
  • Maintain an in-depth knowledge of the banking system and current/future payment options
  • Communicate effectively with all relevant stakeholders of changes, ensuring clarity in timelines, training, and expectation.
  • Demonstrate commitment to the creation of a respectful workplace
  • Maintain thorough knowledge of and adhere to credit union policies and procedures on risk management, confidentiality, security and fraud prevention
  • Acts as an ambassador for the credit union through professional and personal involvement in the community and credit union system
  • Maintain familiarity with the credit union's history, mission, vision and values

This list is not inclusive, and your supervisor may assign other tasks or responsibilities.

Essential Qualifications

  • 2 – 4 years' experience as a Data Analyst in a complex environment.
  • Proven expertise working in the field of Data Analytics with a strong focus on problem solving and deep-dive analysis.
  • Knowledge of statistics, probability and hypothesis testing.
  • Collect and analyze large datasets to identify trends and patterns. Use LLMs to identify trends in data and leverage intuition to find opportunities to improve the user experience in data-related features. Build POCs to demonstrate the feature opportunities identified during data analysis leveraging AI.
  • Cultivate a data-driven mindset within the organization by standardizing metrics and promoting a shared understanding of business performance.
  • Pioneer innovative solutions to complex challenges by structuring problems, developing hypotheses, and designing actionable experiments. Drive business decisions with data-backed insights.
  • Ability to create project plans or specification documents based on a stated business need.
  • Strong analytical, problem-solving, critical thinking skills, work independently and collaborate with team.
  • Strong SQL skills include querying complex datasets from various sources. Advanced proficiency in programming and statistical analysis.
  • Advanced experience in SQL and BI reporting and visualization tools (e.g. PowerBI, DataGrip, etc) as well as experience using DAX
  • Proficiency in R statistical programming to explore diverse data sets and create models using correlation analysis, regression modeling and cluster analysis.
  • Effective communication skills to present data insights to stakeholders clearly.
  • Assist in training new team members to department standards
  • Strong knowledge of Access Credit Union's products and services
  • Advanced knowledge of risk management within the financial industry. Requires strong regulatory knowledge (i.e. PIPEDA, The ACT, OSFI) when creating modelling and other.

Employee Sub-Type

Regular

Starting Salary

$69,929.00

If you are interested in this position, apply today