Deskripsi Pekerjaan
Join MR.DIY as a Data Scientist specializing in Category Optimisation & Allocation, where you'll transform raw data into strategic retail intelligence. This pivotal role bridges analytics and business operations, enabling data-driven decisions that enhance product assortment, inventory efficiency, and customer satisfaction across our Southeast Asian footprint. You'll collaborate with merchandising and supply chain teams to identify market trends, optimize category performance, and align inventory allocation with dynamic consumer demand.
As a key member of our data science team, you'll develop predictive models to forecast sales, analyze competitor landscapes, and identify growth opportunities in fast-moving consumer goods. Your expertise will directly impact MR.DIY's market expansion strategy while ensuring operational excellence through data-backed category management. This position offers the chance to work with cutting-edge analytics in a dynamic retail environment where your insights shape real-world business outcomes.
Tanggung Jawab
- Analyze sales data and market trends to optimize product category performance and assortment strategies
- Develop predictive models for demand forecasting and inventory allocation across multiple locations
- Collaborate with cross-functional teams to implement data-driven category management plans
- Create performance dashboards and reports tracking KPIs like sell-through rates, inventory turnover, and category growth
- Conduct A/B testing and statistical analysis to evaluate category strategy effectiveness
- Identify opportunities for margin improvement and cost optimization through category analytics
- Stay current with retail analytics trends and emerging technologies in category management
Kualifikasi
- Bachelor's degree in Data Science, Statistics, Computer Science, or related quantitative field (Master's preferred)
- 3+ years of experience in data science or analytics, preferably in retail/e-commerce
- Proficiency in Python, R, and SQL for data manipulation and modeling
- Strong knowledge of statistical analysis, machine learning algorithms, and forecasting techniques
- Experience with data visualization tools (Tableau, Power BI) and business intelligence platforms
- Ability to translate complex data insights into actionable business recommendations
- Excellent problem-solving skills with attention to detail and accuracy