Lead Data Scientist (Retail & Wholesale, AI Initiatives), Lotus's

About the Role

Lead Data Scientist to drive end-to-end AI and Advanced Analytics initiatives supporting CP Axtra's Retail & Wholesale businesses (Lotus's). Own AI strategy, delivery, and scaling to generate measurable revenue growth, cost efficiency, and improved customer engagement.

Responsibilities

• Drive AI strategy and roadmap, staying updated on global/local AI trends including Generative AI, personalization, forecasting, and optimization.
• Lead design, development, and deployment of ML/AI models (personalization engines, pricing optimization, demand forecasting, inventory management, GenAI/NLP applications).
• Oversee experimentation, validation, monitoring, and productionization of AI/ML models to ensure scalability, reliability, and business integration.
• Collaborate closely with Data Engineering to enable robust data pipelines and MLOps for production-grade solutions.
• Partner with Retail Operations, Marketing, Sales, Supply Chain, Finance, and IT to co-create use cases, drive adoption, and act as a trusted advisor to senior executives.
• Mentor and coach data scientists and analysts; promote cross-functional collaboration, knowledge sharing, and build internal AI/ML capability.
• Define and monitor success metrics (sales uplift, campaign ROI, cost reduction, customer lifetime value) and continuously optimize AI-driven processes.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, Economics, or a related field.
• 5+ years of experience in data science, advanced analytics, or AI applications; experience in Retail or Wholesale preferred.
• Proven track record delivering AI/ML solutions from ideation to production with measurable business outcomes.
• Strong stakeholder management and communication skills; ability to translate complex AI insights into actionable recommendations.

Technical Skills

• Proficiency in Python, R, SQL and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
• Familiarity with GenAI and NLP frameworks (LLMs, LangChain, RAG pipelines).
• Experience with cloud-based data platforms (AWS, GCP, Azure) and big data technologies (Spark, Hadoop, Databricks).
• Experience with data visualization tools (Power BI, Tableau) and modern MLOps practices for production deployments.

Benefits

• Health Insurance (OPD, IPD, Emergency OPD) via group insurance.
• Provident Fund: 3% contribution.
• Year-end variable and performance bonus.
• Attractive annual leave (minimum 16 days) and no overtime; 5-day work week.
• Free car parking.
• Diverse, non-hierarchical, agile culture with growth opportunities.