Manager, Analytics Consulting
T
Tiger AnalyticsAnalytics Consulting
CanadaFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 8-10 years of experience
- Required Skills
- PythonSQLBusiness AnalysisData AnalysisMicrosoft ExcelStakeholder managementGenerative AI
Requirements
- 8-10 years of experience in business analytics, strategy/management consulting, commercial analytics, operations, supply chain, finance, marketing/customer analytics, product management or similar.
- Strong business curiosity and problem-solving ability.
- Experience working directly with business stakeholders and senior leaders.
- Strong analytical orientation and comfort working hands-on with data.
- Ability to move from business question to hypothesis, analysis, insight, and decision.
- Ability to challenge stakeholders constructively rather than simply accepting requirements.
- Comfort operating with ambiguity and solving loosely defined problems.
- Strong written, verbal and executive communication skills.
- Working familiarity with analytical tools such as Excel, SQL, BI/visualization tools, and/or Python.
- Strong interest and hands-on aptitude with GenAI, AI agents, and emerging productivity/development tools.
- Ability to learn new technologies quickly without needing to be a deep software engineer.
- Ability to bring together business, analytics, technology and specialist teams to deliver solutions rapidly.
Responsibilities
- Engage business stakeholders to understand objectives, economics, processes, constraints and the decisions they are trying to make.
- Ask the right questions, challenge assumptions and convert ambiguous business issues into clear hypotheses, analyses and decision frameworks.
- Explore and interpret data, conduct rapid analyses, identify patterns and translate findings into business implications and recommendations.
- Use GenAI, Agentic AI, analytics and low-code/no-code tools to rapidly explore ideas, analyze information and develop working prototypes.
- Recognize when deeper expertise is required and effectively leverage data scientists, engineers, domain experts, product teams and AI agents.
- Communicate findings in simple business language, recommend actions and work with stakeholders to translate recommendations into measurable business outcomes.
- Rapidly experiment with emerging AI and technology capabilities and identify where they can materially improve business decision-making.
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