head of data & analytics - 1.1m in Hong Kong

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job details

hong kong
information technology
job type
reference number
pearl ku, randstad hong kong
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job description

Our client seeks to become an insights-driven business – harnessing and applying data and analytics to differentiate our products and customer experience to create a competitive advantage. Working with business leaders and stakeholders, the Head of Data & Analytics is responsible for developing and executing data & analytics capabilities across five competencies:

  1. Strategy
  2. People
  3. Technology
  4. Process
  5. Data
We are seeking a candidate who is a data scientist by experience or training and has previously built a data analytics practice. The ideal candidate understands the power of data, including personal experience building algorithmic models, which ideally utilize the latest tools, including artificial intelligence and machine learning. They will also have a technical background in statistics and be proficient in programming languages such as SQL and Python. The ideal candidate will likely have experience in market segmentation and marketing campaign.


Strategy: Elevate insights and data to create competitive opportunities, applying insights at every decision

Analyze data to derive insights that inform business decision making, customer experiences, and innovation to create sustained differentiation and advantage.
  • Identify ways to innovate and create differentiation through the use of insights.
  • Monetize data assets to drive top and bottom line growth and establish framework to measure and track results.
  • Drive improved business outcomes by connecting data, insight, and action.

People: Create cross-functional insights team and help drive culture change

Establish a Data & Analytics team to analyze data to inform decisions and experiment, learn, and collaborate on insights. Build organizational consensus and cross-functional alignment to facilitate the application of continuous optimization across operational and businesses units.
  • Support teams across the enterprise with data engineers to help with sourcing and transformation of data.
  • Encourage teams across the enterprise to continuously experiment and learn from mistakes.
  • Build an insights driven practice composed of cross-functional experts (e.g., people from business, marketing, operations, or products working with data engineers, data scientists, and software developers).

Technology: Implement a technology architecture

Build systems of insight (SOIs) i.e., data, analytics, and learning systems - where the technology resides in an integrated architecture that allows data and insights to flow between multiple application areas. Integrate SOIs with systems of engagement (SOEs), business applications and customer engagement points that allow insights to directly drive decisions, experiences, and actions.
  • Link the success of insights practice to business outcomes.
  • Regularly review and adjust the insights practice to changing business demands.
  • Act on insights to continually optimize business outcomes.
  • Embed data stewardship and governance into business processes (i.e., rather than making it an IT or other department's responsibility).
  • Use software to build systems of insight that connect data, insight, and action.

Data: Capture, manage, and secure data from all sources and make it accessible for insights

Democratize the access of the right data across the entire enterprise by embedding data within applications and allowing different groups across the enterprise to independently access, manage, and combine different data types for insights that are relevant to them. Embed compliance and security protocols throughout the insights generation cycle.
  • Use available enterprise data to inform critical business functions.
  • Leverage groups across the enterprise to perform all three data activities: access data, manage data, and prepare data.
  • Combine different types of data for analysis (e.g., structured data, unstructured data, customer data, web visitor data, and/or advertising data).
  • Manage data and analytics assets securely (e.g., customer data, analytics models, and business rules).
  • Integrate data, analytics, and engagement technologies to optimize experiences and business outcomes.


The Head of D&A must possess and will be measured by the following experience & skills:

  • 3+ years’ experience on a management role in leading a Data & Analytics practice focused on driving business value
  • Demonstrated effectiveness linking the D&A strategy with the needs of business stakeholders, customers and users.
  • Established track record of creating specific competitive advantages through actionable insights from analytics, employees and customers
  • Interest and willingness to start where we are and build a robust practice – entrepreneurial spirit
Structure and people
  • Experience working with senior-level leadership on D&A strategy and execution, including value reporting
  • History of talent development, acquisition and retention
  • Experience working closely with business stakeholders and external partners to align strategy, drive commitment, and participation
  • Experience working in an agile environment supporting cross-functional and integrated product teams that involve all stakeholders to execute quickly
  • Knowledge and experience with cultural and organization change experience going through a reskilling of data engineers and insights staff and assigning new roles to support an insights-driven approach
  • Extensive knowledge and track record of measuring the impact of applied insights, and optimizing in agile cycles of experimentation and learning.
  • Experience creating insights from customer data and awareness that drive action
  • Experience implementing repeatable processes and frameworks to align the organization on actions and outcomes that matter most - creating the connection between the insights they receive and the actions they could take
  • Track record of adopting and regularly using state-of-the-art tools to connect data from multiple systems and creating consolidated dashboards that provide an easy-to-interpret picture of how things are going
  • Track record of leveraging predictive analytics to turn data into customer-led insights, which underpins decisions and action
  • Experience building systems of insight to consistently turn data into action – leading an insights-to-execution process to embed insights in software, digital experiences, and everyday work
  • Experience assembling a digital insights architecture from new and existing technology - making data and insights accessible to all, translating insights into actions, and enabling a learning path to improve data and insights over time
  • Track record of continuous and passionate learning - keeping up with evolving technologies and techniques and willing to experiment with them to test what would work for the business
  • Excellent oral and written communication skills
  • Experience presenting, teaching, mentoring, and facilitating
  • Experience communicating and removing impediments across an organization
  • Demonstrated leadership abilities

To apply online, please click on the link below. Alternatively, for a confidential discussion please contact Pearl Ku on +852 2232 3477.


Artificial intelligence, business intelligence, tableau, python, r, sas, sql, qlikview, data scientist, data science, analytics, customer segmentation, marketing campaign