I will do machine learning and llms models
About this Gig
Data Scientist | Machine Learning & AI Solutions
I am a physicist with a strong background in mathematics and applied statistics, passionate about Data Science and Artificial Intelligence. I specialize in building advanced Machine Learning solutions to help businesses make data-driven decisions and optimize their processes.
What I can do for you:
- Develop supervised and unsupervised Machine Learning models
- Build classification models (binary and multiclass)
- Perform customer segmentation using clustering techniques
- Create recommendation systems
- Forecast time series data for business insights
- Design and implement end-to-end data pipelines (ETLs) in SQL
Technical Expertise:
- PySpark, AutoML, SpaCy (NLP projects)
- Advanced Machine Learning algorithms
- NLP: LLMs (LLAMA, GPT), RAG (LangChain)
- Web Scraping and data extraction
- Object-Oriented Programming (OOP)
- Docker for scalable and reproducible solutions
Proven Experience:
- Churn prediction models
- Insurance propensity models
- Recommendation engines
- Complex data processing and transformation workflows
I bring a physics-driven mindset to Data Sciencecombining analytical rigor with creativity to solve complex problems. My goal is to deliver inno
Programming language:
Python
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SQL
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Colab
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MLflow
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Other
Frameworks:
Scikit-learn
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Keras
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Panda
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Other
Tools:
Jupyter Notebook
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TensorFlow
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Excel
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MLflow
•
Colab
My Portfolio
FAQ
What data do you need from me to start?
I’ll need your dataset, preferably in CSV, parquet, Excel, or any format that works for your project, along with a brief description of your project goals. I can guide you if you need assistance gathering the data.
Can we discuss the project before placing an order?
Of course! Feel free to message me, and we can discuss your project in detail. I’m happy to clarify any questions before you place the order.
Do you offer post project support?
Yes! I provide ongoing support for any adjustments or assistance you may need after the project is completed. This support is included as part of the revisions covered within the package.

