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$
USD
I will predict sales and revenue with ml, optimize inventory and cash flow
Data Scientist Helping Ecommerce Optimize Sales, Pricing and Inventory
I'm Kris, a data scientist specializing in AI-powered solutions for e-commerce businesses. I help companies boost revenue, optimize inventory, and make smarter pricing decisions using machine learning...
About this Gig
Still forecasting sales with spreadsheets? My AI-powered forecasting models deliver 85%+ accuracy so you can optimize inventory, plan budgets, and reduce stockouts.
WHAT YOU GET
- Product-Level Demand Forecasting
- Revenue Projections
- ML Models
- Interactive Dashboard - Visualize trends, seasonality, forecast accuracy
- Actionable Insights - When to restock, budget recommendations
- Full Documentation - Jupyter notebook explaining every step
HOW IT WORKS
- Data Analysis -I clean your sales data and identify patterns
- Model Building -ML algorithms trained on your historical data
- Validation -Test accuracy on holdout data to ensure reliability
- Delivery Forecasts + Dashboard + Implementation guide
PERFECT FOR
- E-commerce managers planning inventory
- Finance teams building revenue budgets
- Shopify/Amazon sellers optimizing stock levels
- Marketing teams aligning campaigns with demand
WHY ME?
- AI Over Excel - Machine learning beats manual projections
- Business-Focused - I deliver actions, not just numbers
- Accuracy Metrics - MAPE, RMSE, MAE clearly reported
- Clean Data Handling - I fix messy/incomplete datasets
Share your sales timeframe, # products, and forecasting goal so I can recommend the right package
Programming language:
Python
•
MATLAB
•
SQL
•
Colab
•
MLflow
Frameworks:
Scikit-learn
•
Google ML Kit
•
PyTorch
•
Panda
APIs:
Other
Tools:
Jupyter Notebook
•
MLflow
•
Colab
My Portfolio
FAQ
What sales data do I need to provide?
Minimum: 6-12 months of sales history with dates, product IDs, quantities/revenue, and prices. Ideally: promotions, marketing spend, and seasonal factors. I'll guide you on format after you order and can work with messy data.
How accurate will the forecasts be?
Accuracy depends on data quality and consistency. My models typically achieve 85-92% accuracy (MAPE 8-15%). I'll provide performance metrics and confidence intervals so you know the reliability of each forecast.
Can you forecast sales for new products with no history?
Yes, using similar product patterns and category trends. For brand-new products, I'll use comparable item data and market benchmarks. Forecasts improve as historical data accumulates.
What if I have multiple sales channels (website, Amazon, retail)?
I can combine multi-channel data or forecast each separately. The Standard/Premium packages include channel-specific forecasts and consolidated projections.
Will I be able to update the forecasts myself later?
You'll receive the trained model and code. Premium tier includes a retraining guide so you can update forecasts as new data comes in. I can also offer post-delivery support for updates.
