Senior Data Analyst

Responsibilities

• Business and Data Landscape: Apply in-depth knowledge of the business, evolving data landscape, tools, and technologies to proactively identify opportunities and address business questions across multiple areas. Determine the scope of business and data requirements, source and integrate relevant data, develop appropriate data frames and analytical solutions, and articulate connections between business topics, relevant data, and analytical frameworks.
• Customer/Stakeholder Orientation: Act as a trusted advisor by understanding customer needs and perspectives, validating and advising on requirements, and providing actionable insights. Lead discussions with customers and stakeholders to interpret analytical results, develop insights, and articulate pragmatic recommendations.
• Expertise in Data: Establish expertise in data sources, formats, and data quality issues. Evaluate data sufficiency, address data integrity, quality, and access issues, and build needed data pipelines or integrations. Lead the development of initial/prototype data models and tools to aid business decision-making.
• Data Analysis: Apply optimal analytical and statistical techniques to execute complex analyses involving multiple data sets and sources. Interpret results within relevant business contexts and provide actionable recommendations. Identifies gaps in analytical tools and models and guides others to do the same, provides feedback on features and/or functions, and recommends changes to architecture, tools, and/or techniques to collect, analyze, and share data-driven insights, while ensuring alignment with business and/or research needs. Anticipates the risks of data leakage, analytical tradeoffs, methodological limitations, etc., and can guide teammates on solutions.
• Reporting and Sharing Results: Share insights through dashboards, reports, data visualizations, interactive self-service platforms, and other means. Actively supports efforts to improve the efficiency of insights reporting, guides others, and drives active relationships across stakeholders to ensure data and related insights are accessible and provide information accurately, clearly, and in an appropriately relevant and timely manner to influence decision making for intended audience(s).
• Experimentation and Innovation: Provide recommendations for experimental design and the development of prototypes/proofs of concepts. Independently assesses and takes calculated risks, and applies previous learnings to influence mitigation plans. Proactively synthesizes and connects results across experiments and identifies relevant connections to other work to make data-driven recommendations that drive the achievement of strategic business goals, as well as potential opportunities for improvements and future research.
• Improvement and Efficiency: Implement methods to create efficiency in analytics and reporting, automate ad-hoc analyses, and share critical domain expertise. Lead the peer review process and auditing of others' work to ensure quality and relevance of analyses.
• Data Model Evaluation: Conduct thorough reviews of data analysis and analytical modeling techniques. Ensure alignment on definitions and standards across stakeholders, and decide on next steps based on assessment results. Identify new evaluation approaches, metrics, and methodologies.
• Orchestration and Collaboration: Establish and leverage working relationships within and across teams to ensure alignment and quality execution of data sourcing, methods, model development, and application. Provide guidance on the adoption of recommended data sources and analytical best practices.
• Data Privacy and Governance: Maintain expertise in data privacy and security requirements, responsible and ethical data handling, and AI practices. Guide others to uphold and apply updated data privacy and governance standards.
• Other: Embodies company culture and values.

Qualifications

• Bachelor's Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 6+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis
• OR Master's Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 4+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis
• OR equivalent experience.
• Candidate must be willing to work at least 50% of the time in United States (PST) based hours.