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Data Science Manager



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3-8 Years
a month ago
56 Viewed
0 Applied

Job Description

Job Purpose:

  • The Data Science Manager is crucial within the D&T department at HEINEKEN International, spearheading the APAC Data & Analytics Hub. It is central to operationalizing our strategy of establishing standardized and scalable data foundations across the region and enterprise. Renowned for delivering cutting-edge innovation, robust technology, and advanced analytics, the D&T department equips HEINEKEN with a significant technological advantage, aligning with our ambitious organizational goals.
  • The role in as part of the APAC Data & Analytics Hub is critical in Heineken to operationalise our strategy of standardised and scalable data foundations across the region and enterprise. The role holder will work with colleagues across Heineken as part of a team that drive the Research & Development activities of the Advanced Analytics organization by identifying and developing new Analytics opportunities for the enterprise within a specific Function or a group of Functions.
  • It is essential that the role holder delivers analytical solutions that are both theoretically sound but create immediate business value. This will be achieved by building strong relationships and collaboration with members of the broader HEINEKEN data organisation including Insight Enablement, Data Management and Global Analytics and various programs across the central, regional and Operating Company (OpCo) structures.
  • In particular, he/she will partner with a growing group of data professionals such as Data Engineers, Machine Learning Engineers and Product Managers who play a crucial role in the development and delivery of Analytics products at scale.

Key Responsibilities:

  • Responsible for R&D within the Advanced Analytics organization for a specific product across a range of products or functions.
  • Apply software engineering best practices (CI/CD and unit testing) to ensure the reliability and robustness of data science solutions.
  • Develop predictive models and only standardised value-measurement techniques (e.g. running A/B testing) to solve complex business problems, such as forecasting timeseries, churn prediction.
  • Coordinate scrums and ensure others have defined scope and clear objectives).
  • Manage portfolio of AA prototype products (pilots) to identify next high value product for HEINEKEN).
  • Relationship creation and management of broader teams stakeholders to ensure strong connection and collaboration for team).
  • Management and/or development and capability building of Junior/Senior Data Scientists (team of 4).
  • Potential responsibility for selection of AA Vendors and AA Tooling workbench (Procurement & Enablement of tools sits with GIS).

Job Requirements:

Education & Experience:

  • MSc/PhD in Statistics, Mathematics, or a related field; equivalent work experience accepted.
  • 8+ years in a pure analytical/science role and 3+ years of management experience
  • Past record of successful Data Science projects
  • Excellent written and verbal communication skills
  • Breadth and Depth in Data Science and Machine Learning
  • Ability to build and maintain strong collaborative relationships with stakeholders across the business
  • Demonstrated ability to effectively manage multiple simultaneous projects and deliverables
  • Communicate effectively with various stakeholders, tailoring your message to your audience's level of technical understanding.
  • Knowledge of industry trends and demonstrated commitment to stay up to date on new technologies
  • Knowledge of Machine Learning, Statistics, and related fields.
  • Fluent Python and thorough knowledge of pandas & scikit-learn.
  • Excellent written and verbal English and local language.

Nice to have:

  • Experience with Azure development environment
  • Experience working with a large development team (CI/CD)

Working Condition:

  • Office-based role (with Hybrid Working) with standard working hours in Ho Chi Minh head office.

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Last Updated: 06-06-2024 10:53:12 AM
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