You will get a professional audit of your Python AI or data science project
Project details
You will get a professional audit of your Python AI, machine learning, forecasting, analytics, or dashboard project.
I will review your codebase from both a technical and practical delivery perspective, focusing on code quality, project structure, model validation, reproducibility, documentation, and maintainability.
This service is suitable if you have a Python notebook, Streamlit app, ML model, forecasting pipeline, analytics script, or early-stage AI/data science prototype that needs to be reviewed, cleaned up, or made more professional.
Depending on the package selected, I can provide a written audit, improvement roadmap, refactoring recommendations, validation/testing guidance, documentation improvements, and selected code restructuring.
My background combines PhD-level applied mathematics, Python data science, machine learning, risk modelling, forecasting, and production-oriented analytics development. The goal is not just to point out issues, but to give you a practical path to make your project more reliable, understandable, and client-ready.
I will review your codebase from both a technical and practical delivery perspective, focusing on code quality, project structure, model validation, reproducibility, documentation, and maintainability.
This service is suitable if you have a Python notebook, Streamlit app, ML model, forecasting pipeline, analytics script, or early-stage AI/data science prototype that needs to be reviewed, cleaned up, or made more professional.
Depending on the package selected, I can provide a written audit, improvement roadmap, refactoring recommendations, validation/testing guidance, documentation improvements, and selected code restructuring.
My background combines PhD-level applied mathematics, Python data science, machine learning, risk modelling, forecasting, and production-oriented analytics development. The goal is not just to point out issues, but to give you a practical path to make your project more reliable, understandable, and client-ready.
What's included
| Service Tiers |
Starter
$350
|
Standard
$950
|
Advanced
$1,750
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 2 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 4 |
Number of Graphs/Charts | 1 | 2 | 4 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$150 - $250
Additional Revision
+$100
Additional Graph/Chart
+$50
Model Documentation
+$145
Source Code
+$120Frequently asked questions
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MI
Massab I.
Jun 10, 2026
Machine Learning Model Troubleshooting
Shoaib did an outstanding job on my machine learning project. They delivered clean, well-documented code ahead of schedule and achieved excellent model performance.
NY
Niam Y.
Jan 6, 2026
Senior Developers from Europe for Short Research Interview
About Muhammad
AI Systems Engineer | Forecasting, Risk Models, ML & Python Dashboards
100%
Job Success
Motherwell, United Kingdom - 5:24 pm local time
I help clients turn messy operational data, technical ideas, or research models into working dashboards, APIs, reports, and production-ready analytics pipelines.
I am a PhD-trained applied mathematician and AI/data science specialist with 20+ years of modelling experience across machine learning, predictive analytics, quantitative modelling, simulation, operational analytics, and real-world decision-support systems.
I can help with:
• Predictive analytics and forecasting
• Machine learning model development and validation
• Python dashboards using Streamlit, Plotly, pandas, and NumPy
• Risk scoring systems and decision-support tools
• Quantitative finance and simulation models
• Data cleaning, feature engineering, and pipeline design
• AI/LLM-assisted analytical tools
• Model benchmarking, testing, documentation, and handover
Selected projects:
1. Heston Model Calibration
Built a reproducible quantitative finance calibration framework for the Heston stochastic volatility model using Fourier pricing, constrained numerical optimisation, multi-start robustness checks, and diagnostic visualisations.
2. Probabilistic Renewable Dispatch
Developed a Python decision-support system for renewable energy forecasting, uncertainty calibration, and risk-aware dispatch planning using probabilistic forecasts, conformal calibration, optimisation, Streamlit, and FastAPI.
3. Latent Performance Benchmarking
Created a portfolio benchmarking framework using Fama-French-style models and stochastic frontier decomposition to separate systematic exposure, noise, and latent performance shortfall.
4. Sensor-Driven Risk Scoring System
Built an industry time-series analytics pipeline combining environmental and occupancy signals to generate operational early-warning risk scores for decision support.
My approach is structured and delivery-focused:
• Clarify the objective, constraints, and success metrics
• Audit and validate the available data
• Build a reproducible modelling pipeline
• Test assumptions and document limitations
• Deliver clean code, clear outputs, and practical recommendations
• Provide handover documentation so the solution is maintainable after delivery
Clients receive robust models, readable code, clear documentation, and outputs that support real decisions — not just notebooks or isolated scripts.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1
I review the project files, setup instructions, data/sample inputs, and stated objectives.
Step 2
I audit the code structure, model logic, data flow, dependencies, documentation, and reproducibility.