VP Enterprise Analytics

POSITION SUMMARY:  The VP, Enterprise Analytics will play a key role in Republic’s digital transformation by building a world-class enterprise-wide advanced analytics team and embedding increasingly sophisticated, real-time intelligence into everything Republic does. The VP will be responsible for driving significant advances in the company’s analytical capabilities to create measurable business value, e.g., enabling operating model transformation, identifying actionable cost-saving and growth opportunities, improving operational efficiency, capturing new customers, etc.   This position reports directly to the SVP Revenue Management and Enterprise Analytics.

PRINCIPAL RESPONSIBILITIES: 

• Develop and implement an advanced analytics (including AI and GenAI) strategy and roadmap aligned with Republic’s strategic priorities.

• Lead the adoption of advanced analytics into Republic’s business by partnering with leaders to identify use cases and prioritizing them based on business impact.

• Work cross functionally with IT and business partners to execute the analytics roadmap and deliver measurable business outcomes.

• Partner closely with stakeholders to integrate the delivery of new analytical capabilities into existing business practices.

• Clearly translate complex analytical insights into actionable strategies for diverse, non-technical audiences, building credibility as a strategic partner.

• Identify emerging technology and advanced analytics trends and pragmatically explore new approaches to leverage data for business advantage.

• Recruit and develop a world-class team by developing strategic university partnerships and active engagement within the broader analytics and data science community.

• Partner with IT and business leaders to increase data literacy across the organization and build a data-insights driven culture.

• Lead Republic’s GenAI Governance Council which is responsible for strategically evaluating and prioritizing new opportunities.

QUALIFICATIONS: 

• Demonstrated ability to identify and develop high-impact analytical solutions to complex operational and business challenges that result in measurable business outcomes.

• Experience in waste management, environmental services, or a logistics-intensive or service-oriented industry is highly desirable.

• Experience in translating business needs to analytic requirements and communicating results of complex analyses to a broad audience.

• Expert-level knowledge of advanced analytics techniques, tools, platforms, and technologies.

• Prior experience as a Data Scientist working on challenging business problems and developing unique solutions.

• Full-stack experience in data collection, aggregation, analysis, visualization, productization, and monitoring of data science products.

• MS in a quantitative field such as computer science, statistics, mathematics, or relevant field.

• Excellent communication skills, both written and verbal, with the ability to translate complex technical concepts to non-technical stakeholders.

• Proven track record of building trust-based relationships with C-level executives, IT and business stakeholders.

• Ability to influence and drive change across multiple departments and functions.

• Adaptability and resilience in a fast-paced, evolving business environment.

• Familiarity with operational challenges and opportunities specific to large-scale logistics and service-oriented businesses.

MINIMUM REQUIREMENTS: 

• 10+ years of relevant experience leading advanced analytics teams that have delivered measurable business outcomes in a data-intensive environment.

• 10+ years of experience leading a team of data scientists and analysts.

Rewarding Compensation and Benefits

Eligible employees can elect to participate in:
• Comprehensive medical benefits coverage, dental plans and vision coverage.
• Health care and dependent care spending accounts. 
• Short- and long-term disability.
• Life insurance and accidental death & dismemberment insurance.
• Employee and Family Assistance Program (EAP).
• Employee discount programs.
• Retirement plan with a generous company match.
• Employee Stock Purchase Plan (ESPP).

The statements used herein are int