I will build a python anomaly detection and forecasting model
Data Scientist, API and Automation Developer, App Builder
Over deze dienst
Are you looking for a Python model that can detect unusual spikes, drops, or performance changes in your business data?
I will build a custom anomaly detection and forecasting solution for your dataset. This is useful for Google Ads performance, sales, revenue, website traffic, conversions, spend, inventory, operations, and other business KPIs.
What I can help you with:
- Anomaly detection for unusual metric changes
- Forecast ranges or expected performance bands
- Time series analysis using rolling windows
- Trend-aware logic for gradual increases or decreases
- Budget-aware or external-factor-aware modeling
- Clean YES/NO review signals for automation workflows
- CSV, Excel, or JSON output files
- Python source code with clear documentation
- Short explanation of key anomalies and outliers
This gig is suitable for:
- Google Ads and marketing analytics
- Sales or revenue forecasting
- KPI monitoring
- Website traffiic anomaly detection
- Business reporting automation
- AI workflow or dashboard inputs
You can send data in CSV or Excel format.
Please message me before placing an order so I can understand your data, goal, and the best approach for your project.
Programmeertaal:
Python
•
R
•
SQL
•
Colab
Frameworks:
Scikit-learn
•
Panda
•
Overige
Tools:
Jupyter-notitieboek
•
Excel
•
Colab
•
RStudio
Mijn portfolio
Andere Data science en ML diensten die ik aanbied
Veelgestelde vragen
What type of data can I send?
You can send CSV or Excel files with time-based data such as dates, sales, revenue, clicks, cost, conversions, website traffic, inventory, or other business KPIs.
Can you work with Google Ads data?
Yes. I can analyze Google Ads metrics such as cost, clicks, impressions, conversions, conversion value, and budget to detect unusual performance changes.
Do you provide the Python code?
Yes, I can provide a clean Python script or notebook with comments and basic documentation.
Can you work with short data history?
Yes. For short histories, I use robust rolling-window and baseline methods. For longer histories, I can use more advanced forecasting or machine learning models.
What output will I receive?
Depending on the package and customisation, you may receive anomaly flags, expected ranges, summary reports, CSV/Excel/JSON outputs, Python code, and documentation.

