I will build machine learning models and predictive analytics in python
About this Gig
Turn your data into predictions you can act on.
I'm a Data Scientist with 6+ years of experience building and deploying ML models in Python and SQL.
What I build:
- Sales and demand forecasting
- Customer churn prediction
- Classification and regression models
- Lead scoring, risk scoring and propensity models
- NLP: text classification, sentiment analysis, NER, summarization
Algorithms: XGBoost, LightGBM, Random Forest, Logistic Regression, time-series models, PyTorch/TensorFlow when needed.
Every project includes:
- Data cleaning and exploratory analysis
- Feature engineering
- Model training, tuning and cross-validation
- Clear metrics (accuracy, F1, AUC, RMSE, MAPE) explained in plain language
- Feature importance so you know what drives results
- Jupyter notebook + clean Python code
Higher packages add a FastAPI prediction API, Docker, and MLflow tracking.
Already have a model? I can also improve, debug or deploy it.
Send me a sample of your data and your goal, and I'll recommend the best approach.
Programming language:
Python
•
SQL
•
MLflow
Frameworks:
Scikit-learn
•
Keras
•
PyTorch
•
Panda
Tools:
Jupyter Notebook
•
TensorFlow
•
Excel
•
MLflow
•
Colab
FAQ
What data format do you accept?
CSV, Excel, SQL database, JSON or Parquet. I can also connect to cloud storage.
Can you guarantee a certain accuracy?
Not before seeing the data. I share a baseline early and explain what is realistic for your problem.
Will I understand the results?
Yes. Every delivery includes a plain-language summary of what the model does and what drives its predictions.
Can you deploy the model so my app can use it?
Yes. The Premium package delivers a ready-to-use FastAPI prediction API with Docker.
