Lead Data Analyst

The Senior Data Analyst is advanced in analytics and is critical for driving improved business performance through advanced statistical and machine learning analytics, predictive modeling, and strategic data visualization. This Analyst will collaborate closely with business leaders and product teams to transform complex data into actionable insights, and will serve as a technical mentor to elevate team performance.

I. Advanced Data Analytics (~65% of Time)

• Consultation & Strategy: Consult with business leaders to drive improved business performance through advanced statistical analysis, machine learning techniques, and operational research.
• Model Development & Enhancement: Provide prescriptive and predictive analytics expertise to support stakeholders in identifying opportunity areas, building robust models, and deploying data-driven solutions.
• AI/ML Tool Utilization: Leverage AI-assisted development tools such as Microsoft Copilot, Databricks AI, and similar platforms to accelerate model development, code generation, and insight delivery.
• Statistical Testing: Design and execute rigorous statistical tests (A/B testing, hypothesis testing, regression analysis, significance testing) to validate findings and support data-driven decisions.
• Data Sourcing & Integration: Research, identify, and integrate new data sources and analytics pipelines to support strategic analyses and enhance existing models.

II. Communication & Influence (~25% of Time)

• Communication & Storytelling: Develop compelling presentations, reports, and narrative documents that translate complex analytical results and model outputs into clear, actionable business stories for diverse audiences - from frontline teams to executive leadership.
• Collaboration: Partner within cross-functional product teams to deliver and communicate outputs of advanced analyses in support of business priorities and product optimization.
• Organizational Influence: Drive adoption of data-driven decision-making across the organization, advocating for best practices in model consumption, insights application, and analytical rigor.

III. Team Mentoring & Development (~10% of Time)

• Peer Mentoring: Provide guidance and technical mentorship to junior and mid-level analysts, conducting code reviews, sharing best practices, and supporting skill development in analytics and AI/ML.
• Knowledge Sharing: Lead internal knowledge-sharing sessions, document reusable frameworks, and contribute to building a stronger analytical culture within the team.

• Experience: 6+ years of professional experience in advanced data analysis, machine learning, or a related analytics role.
• Education: Master’s degree in Data Science, Analytics, Machine Learning, Statistics, or a related quantitative field required.
• Technical Skills:
• Expert proficiency in Python for data analysis and modeling
• Strong experience with Databricks or similar distributed computing/cloud platform.
• High proficiency in reporting tools (e.g., PowerBI).
• Analytical Skills: Expertise in statistical analysis, predictive modeling, machine learning algorithms, and data manipulation (e.g., SQL).
• Business Acumen: Strong understanding of business performance drivers and the ability to translate technical findings and complex models into clear business implications.
• Communication: Excellent verbal and written communication skills with the ability to present complex data and model concepts clearly to executive leadership.
• Mentoring: Demonstrated ability to mentor peers, conduct code reviews, and contribute to team skill development.
• AI/ML Tools & Prompting Expertise: Demonstrated experience using AI assisted development tools (e.g., Microsoft Copilot, Databricks AI, or similar platforms), including the ability to craft effective prompts to accelerate model development, code generation, analysis workflows, and insight delivery., Education: Bachelor’s Degree