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English
$
USD
I will forecast demand and optimize inventory using python
Optimization and Decision Science Consultant
I help industrial teams turn data and operational constraints into practical decisions. My background blends Industrial Engineering, Operations Research, and Computer Science. I specialize in optimiza...
About this Gig
Stockouts, excess inventory, or uncertain demand tying up cash?
I turn historical sales or demand data into validated forecasts and practical inventory decisions.
I can provide:
Data-quality and demand-pattern analysis
Trend, seasonality, intermittency, and outlier detection
Statistical, time-series, regression, and machine-learning models
Backtesting with MAE, RMSE, and MAPE
Forecast charts and confidence intervals
Safety stock, reorder points, EOQ, and service-level recommendations when data permits
Demand, lead-time, and service-level scenarios
Depending on the package, you may receive visualizations, documented Python code, inventory recommendations, scenario comparisons, and a technical report.
I work with Python, SQL, Excel, Jupyter Notebook, Statsmodels, and scikit-learn. My background combines Industrial Engineering, Operations Research, Computer Science, machine learning, and industrial decision support.
Forecast quality depends on data. I report assumptions, limitations, and validation results clearly.
Please contact me before ordering to confirm the number of SKUs, data structure, scope, and delivery time.
Legitimate business and research use only.
FAQ
Should I contact you before ordering?
Yes. Please send a sample of your data, the number of SKUs, forecast horizon, data frequency, and business objective. I will confirm the appropriate package, scope, and delivery time.
What data do you need?
At minimum, I need historical dates and sales or demand quantities. For inventory recommendations, lead times, current stock, ordering costs, holding costs, and target service levels are also useful.
How much historical data is required?
It depends on the data frequency and demand pattern. More history usually improves seasonality analysis and validation. Send a sample before ordering, and I will assess whether the available data is sufficient.
Can you guarantee forecast accuracy?
No responsible analyst can guarantee future accuracy. I compare suitable models, use backtesting, report error metrics, and explain uncertainty, assumptions, limitations, and data-quality issues clearly.
What counts as one SKU?
One SKU means one distinct product, item, material, or demand series. Different locations may count as separate series when forecasts must be produced independently.
Is the Python source code included?
Documented Python source code is included in the Standard and Premium packages. The Basic package provides the forecast, accuracy metrics, visualizations, and summary without source code.
What is included in a revision?
A revision covers corrections or reasonable adjustments within the agreed scope. New datasets, additional SKUs, different objectives, or substantial model changes require an extra or a custom offer.
