Data Product Manager

Roles and responsibilities

Objectives and Responsibilities

The primary goal is to actualize a vision for managing and disseminating data effectively to empower decision-makers across the organization. This involves implementing robust data visualization and self-service capabilities that allow teams to access insights independently.

A key responsibility is to lead, motivate, and develop the Data Project Managers, fostering a culture of trust and transparency that encourages strategic decision-making. The aim is to create an environment where team members feel inspired to innovate and learn from their experiences.

Another critical aspect of the role involves scoping, designing, and implementing machine learning models to advance the business's strategic initiatives. This includes optimizing algorithms essential for enhancing the customer experience, ensuring that data-driven insights lead to actionable outcomes.

Driving the mission of delivering decision-ready data to all teams is vital. This entails establishing benchmarking processes that promote ongoing tracking, A/B testing, and comprehensive data analysis. By providing accessible, actionable insights, the organization can make informed decisions and enhance overall performance.

Effective communication with various stakeholders throughout the business is essential. This role requires aligning diverse perspectives on the value of data and ensuring that everyone understands its significance in driving strategic goals.

Additionally, assessing current business processes, tools, and infrastructure is crucial. This evaluation ensures that CoachHub is equipped with cutting-edge resources necessary to support the vision of effective data management and utilization.

Desired candidate profile

Required Qualifications

The ideal candidate will have substantial experience in a senior leadership position focused on data and information management. They should possess the ability to inspire and lead teams, cultivating an environment where individuals feel safe to experiment and learn from their mistakes. Building a deeply trusting team culture that values constant feedback is paramount.

A strong understanding of varying business needs is essential, alongside the capacity to promote cross-functional collaboration that aids decision-making throughout the organization. The candidate should be adept at engaging in and influencing technical discussions related to data warehouse design, ETL processes, data visualization, and machine learning algorithms. Familiarity with A/B testing and data quality assessments is also critical.

Moreover, the candidate must confidently translate business requirements into technical specifications, demonstrating flexibility in communication style to suit different audiences. This ability to bridge the gap between business needs and technical implementation will be key to successfully leading the data strategy and ensuring its alignment with organizational goals.