Senior Analytics Strategy Consultant

Tiger Analytics

Dallas, Northern (TX, KY)

Hybrid

USD 120,000 - 160,000

Full time

14 days+

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Job summary

Tiger Analytics in Dallas is seeking a business-first, analytically strong consultant to work directly with business leaders to translate complex needs into data- and AI-enabled solutions. You will understand how the business operates, identify critical decisions, determine required information and analyses, and mobilize AI/Agentic tools and cross-functional teams to deliver results.

Ideal candidates have a strong analytics background, experience with GenAI, and comfort communicating with

Qualifications

8-10+ years of experience in business analytics, strategy/management consulting, commercial analytics, operations, or a similar decision-oriented environment.
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.
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.

Responsibilities

Understand the business and the decision: Engage business stakeholders to understand objectives, economics, processes, constraints and the decisions they are trying to make—not simply document stated requirements.
Challenge and structure problems: Ask the right questions, challenge assumptions and convert ambiguous business issues into clear hypotheses, analyses and decision frameworks.
Use data to develop insights: Explore and interpret data, conduct rapid analyses, identify patterns and translate findings into business implications and recommendations.
Rapidly prototype solutions: Use GenAI, Agentic AI, analytics and low-code/no-code tools to rapidly explore ideas and develop working prototypes.
Orchestrate expertise: Leverage data scientists, engineers, domain experts, product teams and AI agents rather than building everything alone.
Drive from insight to action: Communicate findings in simple business language, recommend actions and translate into measurable outcomes.
Continuously learn: Rapidly experiment with emerging AI technologies and determine where they improve decision-making.