Location
Ottawa, ON | Canada
Job description
Job Description
The Manager, Product Analytics shapes the way product performance is measured, defines what questions should be asked, and scales analytic methods and tools to support the business. Responsible to define and track KPIs, support strategic initiatives, design experiments, evaluate A/B tests, implement data instrumentation, and informs on investment. The Manager is a “full-stack” data powerhouse who uses data, to drive high quality and velocity decision-making that enables the creation and development of the best products for Canadian consumers, businesses, and communities. Provides core input to decision-making across all major product strategies and initiatives in collaboration with product managers, business/strategy managers, operations, engineering, and leadership across Canada Post.
Below are the main job requirements and responsibilities for the Manager, Product Analytics:
1. In partnership with the product leadership team, creates a systemic data-driven approach focused on outcomes delivered from product investments, that measures business and customer impact.
2. Responsible for providing insights to the business product strategies and initiatives, derived from defining and updating core metrics. Builds a culture of data-driven decisions, capitalizing on external best practices, emerging industry trends, and innovative new ways to leverage data to drive revenue and growth. Evaluates and forecasts impact of product features on users, consumers, businesses, and the ecosystem.
3. Develops and establishes analytical framework and roadmap including ad-hoc analysis, automated dashboards, and self-service reporting tools to surface data to partners.
4. Gathers insights, runs rapid experiments, and provides and communicates business and customer outcomes based on qualitative and quantitative data.
5. Dives deep into the data to understand and analyze how behaviors change with the evolution of our products and strategies.
6. Leverages data query tools from multiple sources to amalgamate into new data sets for analytical and modeling purposes and evaluates key performance metrics and trends.
7. Develops analytical models for data generated by a variety of applications and products. Builds analytics applications and visualizations.
8. Performs data mining tasks, such as classification, regression, clustering, recommendations and text analysis.
9. Builds, evaluates and improves various algorithms at the core of existing or new data driven products. Continuously identifies opportunities and solutions to better meet business needs.
10. Manages junior analysts, assigns, approves and certifies work, and provides coaching and development opportunities to broaden skill set and experience.
Education
• Completed post-secondary education in a related field (Data Science, Math/Statistics, Computer Science, Engineering), graduate level preferred
Experience
• 3 to 5 years of analytics experience with the understanding of growth analytics and product analytics.
• Significant experience working with methodologies such as predictive modeling, profiling, cohort analysis, segmentation forecasting, clustering, regression, operations research and data mining
• 2 or more years’ experience managing people
Other Candidate Requirements
• Experience with SQL, Oracle, Teradatastudio, Python, SAS, Business Objects, Tableau, PowerBI and SAP BW preferred
• Experience using analytical concepts and statistical techniques
• Experience using analytics techniques to contribute to company growth efforts, increasing revenue and other key business outcomes.
• Excellent team building and leadership skills and experience
• Broad experience in business management, marketing, planning and finance, operation and project management, intimate knowledge of cross-enterprise functions and operations, is an asset.
• Demonstrated ability to build an analytical plan based on business issues
• Knowledge of IT processes and infrastructure required to support business intelligence and analytics
• Experience building aggregates and optimizing data workstreams
• Experience designing and assessing impact of A/B experiments in a fast-paced product development cycle
• Strong oral and written communication skills
• Technical background and programming experience–especially R or Python or familiarity with machine learning techniques is an asset.
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