Responsibilities

• People Management: Deliver success through empowerment and accountability by modeling, coaching, and caring. Model: Live our culture. Embody our values. Practice our leadership principles. Coach: Define team objectives and outcomes. Enable success across boundaries. Help the team adapt and learn. Care: Attract and retain great people. Know each individual’s capabilities and aspirations. Invest in the growth of others.
• Application of Data: Ensures team members evaluate the sufficiency of data between internal and external sources, drives accountability of identification and resolution of data quality issues, and encourages and coordinates cross team collaboration and data sharing to build data pipelines or integrations. Leverages data, analyses, and learnings to articulate industry- and client relevant stories and insights to various audiences and at industry events.
• Data Analysis: Builds best practices for team members to leverage and apply their expertise across client and business-related analytical needs. Guides and coaches team members through the execution of complex analyses to resolve analytical challenges, interpret results within a client context, and acts on opportunities with actionable recommendations. Supervises team's data analyses, feedback, and that recommendations are accessible and easily understood by the relevant stakeholder groups, and ensures accountability and efficiency in delivering outcomes that are aligned with client, industry, and business needs.
• Data Privacy and Governance: Contributes knowledge across the team in data privacy and governance rules and regulations and guides others to uphold and apply updated data privacy and governance, maintain awareness of where to seek further expertise on such rules and regulations when needed, and leverage personal expertise to identify and share relevant best practices. Identifies appropriate internal and/or external stakeholders to update or improve data privacy and governance practices to better align to industry.
• Continuous Improvement, Efficiency, and Innovation: Guides the team to develop and implement methods that create systematic efficiencies in core work related to analytics and reporting that are reusable, readily discoverable, self-service, and directed to meaningful interpretation of data that drive impactful business decisions across the organization. Coaches team in guiding optimal and innovative methods for operationalizing, sharing, and scaling insights, and coordinates automation of patterns of ad hoc analyses into regular reporting features. Shares thought leadership and partners with leaders to leverage and implement automated methods for use in data collection, reporting, and analysis, while contributing to operational tracking to ensure work actions and decisions are appropriately measured.
• Orchestration and Collaboration: Establishes and leverages strategic working relationships within and across internal and client teams to ensure data sources, methodologies, models, and analytical tools and processes are high-quality, and that recommendations are data-driven and appropriately relevant to clients' industry vertical(s) to consistently drive positive impact. Guides own and team's actions across networks of peers and client stakeholders to leverage resources and solutions that were instrumental to success in similar contexts, and shares expertise on industry vertical, clients, and competitors across teams to inform decision-making related to advanced analyses and their interpretations.
• Presentation of Results: Provides guidance to team members on the development and delivery of compelling and easily understood client-facing presentations of analyses, reports, data visualizations, etc. Provides guidance to team members on how to synthesize insights into a story, and proactively leverages stories to influence leadership and other senior stakeholders' decision-making and drives business outcomes internally, externally, and within industry verticals. Supports efforts to improve efficiency of reporting and presentations, and encourages others to share insights and build presentations that are accessible, that cultivate trust with clients, and that present relevant information accurately, clearly, and appropriately to influence decision-making for intended audience(s).
• Understanding Client's Business: Advances own and team's comprehensive understanding of clients' business knowledge, including industry trends, clients' value propositions, and the competitive landscape to help drive sustainable long-term value over competitor's solutions, address the most impactful business needs, and adapt to anticipated industry trends. Identifies the appropriate scope and impact to develop solutions, builds and leverages connections with client's leadership, and includes appropriate stakeholders in scoping process. Coaches and encourages team members to broaden knowledge of clients' business and industry verticals.

Requirements

• Experience in statistics, mathematics, analytics, data science, data analysis and reporting, business intelligence, business and financial analysis, or related field
• OR equivalent experience.
• Experience using tools such as PowerBI/Tableau, DAX, R, SQL for data manipulation and visualization on large datasets.
• People management experience.
• Effective in communicating complex analyses to a mix of both technical and non-technical partners and clients.
• Experience utilizing analytical tools to turn massive, dynamic datasets into actionable insights.
• Experience pairing data visualization with storytelling to deliver persuasive presentations that influence varying audience levels.
• Experience conducting, interpreting, and clearly communicating measurement analyses (e.g., incrementality, attribution, lift studies) to inform client decisions.
• Experience and proficiency using PowerBI/Tableau, DAX, SQL for data manipulation and visualization. Working knowledge and familiarity in a combination of the following data manipulation and visualization tools is a plus: Python, R, PowerPivot, Microsoft Advertising API.
• Solid knowledge of statistics, predictive modeling and data clustering/classification techniques.

Preferred

• Experience in statistics, mathematics, analytics, data science, data analysis and reporting, business intelligence, business and financial analysis, or related field
• OR equivalent experience.
• Experience in a partner or account management/client service/client-facing role.
• Experience in EMEA market.
• Experience in digital media, data analysis, and data management.