Business Analytics & AI Strategy Lead

Tiger Analytics; Seattle, Northern (WA, KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Tiger Analytics, a leading analytics consulting firm, seeks a business-first consultant who translates complex business needs into data- and AI-enabled solutions in Seattle. You will work with executives to define objectives, structure analyses, and deliver actionable insights that drive real-world outcomes.

The role emphasizes hands-on data work, rapid prototyping with GenAI, and close collaboration with data science and engineering teams.

Qualifications

• 5–10 years of experience in business analytics, strategy/management consulting, or similar decision-oriented environments.
• Demonstrated ability to understand stakeholders and translate insights into business actions.
• Strong analytical orientation with hands-on data work and problem solving.

Responsibilities

• Understand the business and decisions with stakeholders to define objectives and success metrics.
• Structure problems, frame hypotheses, and design analyses to test them.
• Leverage data to develop insights and actionable recommendations for leadership.
• Rapidly prototype AI-enabled solutions and low-code approaches to test ideas.
• Collaborate with data scientists, engineers, and product teams to implement solutions.
• Communicate findings in clear business language and drive measurable outcomes.
• Continuously learn about AI advances and apply them to business problems.

Skills

Business analytics

Problem-solving

Executive communication

Stakeholder management

Tools

Excel

SQL

BI/Visualization

Python

Job description

Tiger Analytics, a leading analytics consulting firm, seeks a business-first consultant who translates complex business needs into data- and AI-enabled solutions in Seattle. You will work with executives to define objectives, structure analyses, and deliver actionable insights that drive real-world outcomes.

The role emphasizes hands-on data work, rapid prototyping with GenAI, and close collaboration with data science and engineering teams.