Sr. Manager Data Science (Dark Stores Intelligence)

About the Role
As the leading delivery company in the region, we hold a significant responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to enhance our platform to become more intelligent in how it understands and serves our users.
In the role of Senior Manager Data Science at the Global QC Hub, you will lead and manage a talented machine learning team focused on improving price optimization and boosting operational efficiency. You will collaborate closely with Data Engineers and Data Scientists across the broader data team, as well as with product and business managers throughout the organization.

Responsibilities

• Develop a deep understanding of the processes that comprise QC business products and operations.
• Become familiar with QC’s data platforms and dense data ecosystem.
• Leverage your understanding of QC business and data, combined with your expertise in machine learning, to identify opportunities for substantial business value.
• Set the team's roadmap, define success criteria, and establish priorities in collaboration with engineering and business partners.
• Own the entire ML workflow, including problem formulation, learning task definition, dataset development, modeling approach selection, model training and refinement, evaluation, and production deployment.
• Lead the experimentation and causal inference practice: design and review A/B, multivariate, switchback, and geo experiments, and apply causal methods (incrementality, uplift modeling, matching) to rigorously measure true business impact.
• Oversee data analytics, data engineering, data modeling, and reporting functions.
• Design and develop our ML platform including feature management, continuous training, serving, and integration for online and batch inference use cases.
• Participate in and lead key technical and design decisions, ensuring successful implementation and deployment of ML-based solutions.
• Collaborate effectively with business, product, and engineering managers throughout the lifecycle of ML and data products.
• Balance sustainable practices with high-impact projects while identifying low-cost, high-impact wins to deliver value sooner.
• Coach and mentor ML engineers, data scientists, and data engineers both technically and professionally.
• Manage the end-to-end processes for data analysis, data engineering, and ML development.
• Drive the recruitment and interviewing of top data talent.
• Contribute to the company's overall strategy and technological vision.
• Play a crucial role in developing our organizational structures to keep pace with growth.

Qualifications

• Technical Experience

  • Expertise in both classical and deep learning.
  • Strong experience with classical ML frameworks and deep learning frameworks.
  • Familiarity with classical data structures and algorithms.
  • Experience in deploying and managing production ML systems at scale.
  • Background in recommendation systems, personalization, search, or logistics is highly desirable.
  • Knowledge in process optimization or workflow automation is a plus.
  • Proficient in experiment design and statistical analysis with the ability to analyze A/B and multivariate tests.
  • Strong causal thinking with hands-on experience in incrementality measurement and uplift modeling.
  • Experience in advanced experimentation and causal methods (e.g., switchback testing, geo testing, marketing mix modeling, matching).
  • Experience with data pipelines, data modeling, and data reporting is a plus.

• Education

  • Bachelor's degree in engineering, computer science, technology, or similar (postgraduate degree is a plus but not required).
  • 10+ years of overall experience in software engineering and data across multiple disciplines.
  • 8+ years in machine learning, preferably in a high-growth consumer product company or similar environment.
  • 3+ years in engineering management in ML engineering or a related area.