Principal Data Analyst

Your role:

• Break down highly complex, ambiguous business problems into structured analytical approaches, proposing innovative and technically sound solutions.
• Drive solution discovery with stakeholders by clarifying requirements, defining analytical feasibility, and shaping technical roadmaps for high‐impact initiatives.
• Act as a self‐starter who independently scopes, leads, and delivers analytical workstreams with minimal guidance, while ensuring timely, high‐quality outputs.
• Deliver insights for revenue growth, customer patterns, and operational efficiencies and translate complex data insights into actionable recommendations for technical and non-technical stakeholders, and business leaders
• Build, optimize, and deploy predictive and machine learning models.
• Lead analytics workstreams and collaborate with cross‐functional teams.
• Applies strong financial and analytical judgment to rapidly identify opportunities and act decisively, even when information is incomplete.
• What you bring to the role:
• Bachelor’s degree (master’s preferred) in a quantitative field.
• 8+ years of functional experience, including a minimum of 5+ years of position specific experience in data science or advanced analytics.
• Advanced SQL skills and Experience with GCP (Big Query, VertexAi a plus)
• Proficiency in visualization tools such as Google Looker, Qlik, PowerBI, Plotly Dash
• Strong analytical and modeling skills using Python (for its rich suite of statistical and modeling libraries like numpy, pandas, scikit-learn, etc.).
• Strong communication skills and ability to influence decisions.
• Demonstrates innovative thinking with the ability to challenge entrenched assumptions, navigate ambiguity, and quickly adapt in fast‐changing environments.
• Exceptional storytelling and presentation skills, with the ability to build compelling executive‐ready materials and clearly communicate complex analytical insights to diverse audiences.
• Preferred Qualifications:
• Experience in B2B, distribution, or supply‐chain analytics.
• Knowledge of MLOps and model deployment.
• Exposure to GenAI, LLM workflows, or automation solutions.