About Pharmacity:
Pharmacity is Vietnam's leading pharmaceutical retail chain, committed to providing accessible and high-quality healthcare services to communities nationwide. We are strategically investing in advanced Artificial Intelligence, Machine Learning, and Data Science to power our ambition of becoming the undisputed leader in the omni-channel pharmacy and healthcare platform space, surpassing competitors. We are building a data-driven culture that leverages cutting-edge technology to deliver personalized experiences, optimize operations, and unlock new growth opportunities. We are seeking an exceptional AI/ML & Data Science Manager to lead critical initiatives in this transformation.
Position Summary:
The AI/ML & Data Science Manager will lead a team of data scientists and machine learning engineers, responsible for developing and deploying advanced analytical models and AI solutions that drive significant business impact across Pharmacity's omni-channel platform. This role will specifically focus on solving complex problems related to demand forecasting, enabling Agentic AI capabilities, enhancing personalization for customers, and optimizing healthcare platform upsell and cross-sell strategies. This leader will combine deep technical expertise with strong business acumen and excellent leadership skills to turn data into actionable insights and intelligent products.
Key Responsibilities:
- Strategy & Roadmap:
- Define and execute the AI/ML and Data Science strategy for key business areas, including:
- Demand Forecasting: Develop and implement advanced predictive models to optimize inventory, reduce stockouts, and minimize waste across our vast product catalog (pharmaceuticals, health & beauty, FMCG), accounting for seasonality, promotions, external factors, and unique pharma challenges (e.g., product shelf-life, regulatory changes, varying demand for specific medications).
- Agentic AI: Explore, prototype, and build intelligent agents that can proactively assist customers (e.g., virtual health assistants, intelligent navigators for health information), automate operational tasks, and provide real-time decision support for pharmacists and healthcare professionals on the platform.
- Personalization: Drive the development of sophisticated recommendation engines, personalized content delivery, and tailored customer journeys across all touchpoints (web, mobile app, in-store, CRM), leveraging diverse customer data.
- Healthcare Platform Upsell & Cross-Sell: Design and deploy AI-driven models to identify optimal upsell (e.g., higher-tier health packages, premium products) and cross-sell opportunities (e.g., complementary products for chronic conditions, related health services) within the healthcare platform, enhancing customer value and revenue.
- Translate complex business challenges into data science problems, identifying appropriate methodologies and data requirements.
- Build and maintain a prioritized AI/ML roadmap, aligning with product, engineering, and business stakeholders.
- Model Development & Deployment:
- Lead the end-to-end lifecycle of AI/ML models, from data exploration, feature engineering, model selection, training, evaluation, to deployment, monitoring, and retraining in production environments.
- Ensure models are robust, explainable, ethical, and perform at scale.
- Oversee the integration of AI/ML models into various systems (e.g., e-commerce platform, CRM, inventory management, patient engagement tools).
- Champion MLOps best practices, including version control, automated testing, CI/CD for models, and performance monitoring.
- Team Leadership & Development:
- Build, mentor, and grow a high-performing team of data scientists and machine learning engineers.
- Foster a culture of innovation, experimentation, continuous learning, and rigorous scientific inquiry.
- Provide technical guidance, architectural oversight, and hands-on support as needed.
- Conduct performance evaluations, set clear goals, and support career development for team members.
- Data & Infrastructure Collaboration:
- Collaborate closely with Data Engineering teams to ensure the availability of clean, reliable, and well-structured data for model training and inference.
- Work with the Engineering Director to define the necessary infrastructure for AI/ML development and deployment (e.g., computing resources, data lakes, feature stores).
- Partner with the CRM & CDP team to leverage customer data for personalization and engagement initiatives.
- Stakeholder Communication:
- Communicate complex analytical findings and AI capabilities to non-technical stakeholders in a clear, concise, and actionable manner.
- Collaborate with Product Managers to define user stories and ensure AI solutions meet business needs and deliver measurable value.
- Present key insights, model performance, and ROI of AI/ML initiatives to senior leadership.
