Data Analyst (Hybrid)

Work Flexibility: Hybrid

As a Data Analyst, you will support the collection, analysis, and interpretation of data to provide insights that support business decisions. Working closely with Business Enablement (sales operations), and Commercial Divisions, you will assist in creating reports, visualizations, and data products that align with Canada and Commercial Division strategic goals.

What you will do

• Review basic data and finance concepts and their business impact.
• Support collaboration efforts with partners across functions.
• Assist in gathering, cleaning, and organizing data from various sources.
• Conduct scoping discussions with commercial teams to collect contextual information and identify opportunities where data analytics concepts can be applied to business opportunities.
• Drive external data research relevant to commercial priorities such as gaining competitive analysis and surveillance through variance channels (may include provincial government agencies, web scraping, purchased market data, partnering with relevant Stryker departments to leverage their knowledge).
• Assist in building visualizations in Power BI providing a 360 view of our customer, incorporating external market/competitive data, existing contract data, opportunity pipeline with current order information and other relevant information.
• Help identify white space in our customer base, seeking and sharing opportunities to our commercial team.
• Participate in presentations and communications to the business and stakeholders.
• Support problem solving, root cause analysis, identify potential solutions, and evaluate them against requirements.

What you need

Required:

• Bachelor’s Degree in Computer Science, Data Analytics, Business Analytics, Data Science, Computer Information Systems, or related field.
• Familiarity with business intelligence and visualization/analytics platforms, such as PowerBI or Tableau.

Preferred:

• Experience with data transformation and cleansing concepts as well as relational database and data modeling concepts.
• Experience with data governance concepts including the need for documented definitions, calculations, sources, lineage, etc.
• Knowledge of at least one programming language, central to data analytics, such as SQL, Python, R, Dax or M.

Travel Percentage: None