Job Description: Forecasting Specialist with Expertise in Inventory Management
We are looking for a Forecasting Specialist with a strong background in inventory management and data-driven demand forecasting. This role is focused on optimizing inventory levels and enhancing supply chain efficiency through advanced forecasting models and analytical tools. The ideal candidate will bring expertise in statistical forecasting, data analysis, and technical systems to improve retail inventory operations.
Responsibilities:
Statistical Demand Forecasting: Utilize advanced statistical techniques (e.g., ARIMA, exponential smoothing, seasonal decomposition, regression models) to create accurate demand forecasts and inventory plans.
Inventory Optimization: Apply mathematical models like EOQ (Economic Order Quantity), Safety Stock Calculation, and Replenishment Algorithms to optimize inventory levels and minimize holding costs.
Data Analysis & Reporting: Extract and analyze large datasets from various sources, utilizing SQL and advanced analytics tools to forecast trends, detect anomalies, and ensure inventory alignment with demand.
Forecasting Model Development: Continuously develop, refine, and evaluate statistical models to improve forecasting accuracy and adapt to changing consumer behavior.
System Integration: Work with ERP systems (e.g., SAP, Oracle) and integrate them with forecasting platforms (e.g., Demand Works, Forecast Pro) to streamline inventory management processes and ensure real-time data synchronization.
Automation and Scripting: Write Python or R scripts to automate data extraction, cleaning, analysis, and forecasting tasks.
Data Visualization & Communication: Leverage tools like Power BI, Tableau, or Google Data Studio to build dashboards that present inventory insights and forecasting accuracy to stakeholders in an actionable format.
Continuous Improvement: Apply machine learning techniques (e.g., regression models, decision trees, ensemble methods) to enhance forecasting models and adapt to new retail trends.
Key Technical Skills:
Statistical Tools & Forecasting:
Expertise in R or Python for statistical analysis and time series forecasting.
In-depth knowledge of forecasting techniques (ARIMA, Holt-Winters, Exponential Smoothing).
Understanding of advanced regression and machine learning algorithms applied to demand prediction and trend analysis.
SQL & Database Management:
Proficiency in writing complex SQL queries to extract and manipulate data from inventory and sales databases (MySQL, PostgreSQL, etc.).
Experience working with relational databases and cloud-based solutions for inventory data management.
Inventory Optimization Algorithms:
Advanced understanding of inventory models such as ABC Classification, Just-In-Time (JIT), Reorder Point (ROP), Safety Stock Optimization, and Vendor-Managed Inventory (VMI).
Ability to apply algorithms to dynamically adjust reorder quantities based on fluctuating demand.
Data Visualization & Business Intelligence:
Expertise in data visualization tools like Power BI to present key performance metrics and inventory analytics to non-technical stakeholders.
Ability to create interactive dashboards that display key inventory KPIs (e.g., stock levels, turnover rates, and demand forecasts).
Automation & Scripting:
Proficient in Python (pandas, NumPy) or R for scripting and automating inventory analysis and forecasting processes.
Experience with Jupyter Notebooks or RStudio for developing reproducible analysis workflows.
Additional Skills:
Machine Learning (ML):
Knowledge of machine learning algorithms (e.g., XGBoost, Random Forests, Neural Networks) for improving predictive accuracy in demand forecasting.
Desired Qualifications:
Bachelor's degree in Statistics, Computer Science, Supply Chain Management, or a related field.
Proven experience in a similar technical forecasting or inventory management role, preferably in a retail or e-commerce setting.
Strong problem-solving skills and a keen attention to detail in data quality and accuracy.