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Cards and Payments Data Scientist

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Reporting to the Director Cards and Payments, the Cards and Payments Data Scientist conducts new or enhanced analytical approaches to drive insights to support Direct Banking's overall strategic plans and business objectives. This position is accountable for modeling complex problems, developing predictive systems and identifying opportunities through the use of algorithmic, mining and visualization techniques. In addition to advanced analytic skills, this role is also proficient at utilizing leading edge techniques for analyzing social media, transactional/sales data, unstructured data, market research surveys, employee data and other data sets.

This position utilizes innovative new approaches such as predictive modeling, data and text mining, machine learning approaches, clustering and classification techniques, regression procedures, conjoint/discrete choice modeling, and other techniques to analyze members and prospective members. Data sources include credit and debit card data, call center data, payments data, external market intelligence, internal member data and insights, competitive information, primary and secondary research analysis, internal financial performance and business intelligence reporting. This position also will incorporate third party data on member experience and brand health in conjunction with member attribute measurement in the creation of statistical models of member/prospect behavior. This position is also accountable for the use of data analytics to build and refine the segmentation strategy, branch and market composition, profitability assessment and channel migration (aligning available channels for profitable multi-channel sales/service/segments).

This position supports the Direct Banking team members and works closely with other internal departments, and coordinates cross-functional projects. This position requires the ability to understand business needs - question and translate them into an effective analytics plan, execute the analysis and then translate the findings into strategic insights. This position will support a CRM/MRM implementation and data population.

Direct Banking Analytics

  • Collaborative role in the development, implementation and maintenance of statistical and predictive models to drive incremental sales.
  • Perform exploratory data analysis for new data sources.
  • Extract data and perform quality checks.
  • Mine sample raw data to find anomalies and patterns.
  • Refine segmentation models using a variety of statistical techniques including clustering algorithms and machine learning approaches.
  • Deploy analytical tools and data science techniques to analyze large data sets and develop custom models/algorithms to uncover trends, patterns and insights in the data.
  • Campaign measurement and analysis.
  • Work with different business partners on the application and testing of analytical models.
  • Complete data analytics projects using various methodologies to support strategic and operational decision making and identify market opportunities.
  • Assist with development and implementation of predictive models for cross-sell, up-sell, next best product and member retention.
  • Occasional ad-hoc reporting.

Cards and Payments Research and Competitive Intelligence

  • Analyze member data and research findings, and assist Insights to create cohesive summaries and provide recommendations.
  • Use output from modeling activities to identify areas of competitive advantage with actionable insights to improve the credit union’s success.
  • Studies include but are not limited to:
    • Credit and debit cards, Payments, Call Centre industry market makeup and trends
    • Market share analysis
    • New market assessment
    • Campaign/Advertising modeling
    • Product innovation
    • Segment refinement
    • Member and non-member analyses
  • Support others on the Direct Banking team including the Growth Specialists, as well as internal decision-makers such as the Leadership Team, by integrating member behavioural analysis with analytical market research and trend information.

Member and Database Research

  • Conduct analytical research on credit union members in order to provide insights and direction for tactical implementation of Direct Banking strategies.
  • Use member behavioural and attribute analysis to assist Insights in creating meaningful summaries for branches, business lines, departments and senior management that identify opportunities for the credit union.
  • Provide recommendations on direction and initiatives of company based on analysis of member behaviour and responses to on-going Growth and Operations activities.
  • Studies include but are not limited to:
    • Member loyalty and satisfaction
    • Share of wallet analysis
    • Consumer financial needs and preferences
    • Channel usage patterns
    • Trends in the financial services industry
    • Overlaying 3rd party behavioural and attitudinal information on existing member data

Segment Program Development and Management

  • Develop member insight approaches that drive strategic decision-making and maximize resource efficiency of sales.
  • Perform clustering analysis and utilize other statistical techniques to refine and extend segmentation analysis of the existing membership and external market potential.
  • Identify desired segments that align with corporate objectives, including possible segmentation by life stage (children, youth, seniors), values (eco-green, community, ethnicity) and involvement stage (i.e. new members), and balance that with achievable in-house data and external information availability.
  • Develop and test models based on member segments to grow new members, increase wallet share and retain existing members.
  • Use quantitative analysis to determine relevant member attributes and share with the Direct Banking team for the development of segment-specific campaigns, products and communication.
  • Provide quantitative support to the Market Insights team in the on-going analysis of segments and results of segment-targeted initiatives.
  • Assist in providing key recommendations on member segmentation, branch segmentation, call list and sales lead generation criteria, branch location analysis, campaign structure, and leveraging CRM/MRM data for insights.

Cross-Functional Team Support

  • Work alongside all retail and commercial business lines in conjunction with analyzing member data to understand product needs.
  • Provide consumer and member insights to the Direct Banking team to help ensure maximum return on investments. Activities include:
    • Assess market potential
    • Recommend target groups
    • Contribute to the development of campaign goals
    • Coordinate contact lists
    • Implement traceable measures for campaigns and provide timely measurement of results
    • Create a post-campaign analysis with recommendation for future initiatives
  • Work with key stakeholders in determining consumer cards and payments financial needs and preferences, channel usage, product preference and other consumer insights.
  • Provide product and financial knowledge and develop strong partnerships with key internal partners.

Leadership and Direct Banking Team Collaboration

  • Assist in championing the use of analytics to drive fact-based decision-making.
  • Help foster a healthy team environment.
  • Contribute to and take part in the development of the annual Direct Banking Plan, budgeting and performance metrics.
  • Establish and maintain effective relationships with internal department partners.
  • Attend and fully participate in meetings and activities.

Experience:

  • Minimum of five years’ experience in Credit and Debit Card analytics with a thorough knowledge of quantitative research methodology.
  • Exceptional analytical and conceptual skills – ability to interpret measurement results and understand the business implications.
  • Experience with conjoint/discrete choice modeling, clustering techniques, factor analysis.
  • Strong ability to structure and write queries in SQL.
  • Strong knowledge of statistics and predictive methods such as SEM, multiple and logistic regression, Bayesian modeling, support vector machines, neural net training, tree induction techniques like CHAID, CART, random forest, random tree, etc.
  • Multi-tasking and priority setting – ability to effectively manage multiple projects of varying complexity.
  • Ability to work independently and as part of a team.
  • Able to translate complex data into actionable insights and recommendations.
  • Strong understanding of the Credit card business is required.
  • Experience with cross-sell, up-sell, retention, and customer lifetime value models preferred.
  • Excellent communication skills, both written and verbal.
  • Experience in leading intermediate Data Analysts is preferred.

Education and Training:

  • Undergraduate degree in a quantitative discipline such as Statistics, Econometrics, Mathematics, or equivalent work experience.
  • Advanced level skill in data analytics and programming applications such as SAS, Python, R, and Excel.

Any other special requirements necessary to do the job:

Requires a willingness to work a flexible schedule; may require weekend and / or evening work.

Available to travel, etc.

The business may from time to time ask for branch and/or department support for special projects and/or areas experiencing staff shortages. All employees may be asked to volunteer to assist in areas of need during these times. These assignments could result in a change of hours, location, and/or travel.

Why Servus Credit Union? We live our values in how we do business and how we treat our employees. Servus Credit Union is one of Canada’s 50 Best Managed Companies. Servus is committed to being socially responsible and living the co-operative values. Through our operations, we strive to make a positive impact on our economy, the environment and society. We know that our employees are our most valuable assets so we offer ongoing growth and career advancement and we reward employees for their hard work and achievements.

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