Streamlit Jobs

I need a simple Streamlit dashboard built in Python that loads data from a numpy .npz file and displays investment analysis charts. The dashboard should run locally with streamlit run app.py. What I need: 5 pages using Streamlit multi-page routing. Each page shows metrics and 2-3 Plotly charts for a different asset. The charts are: IRR probability distribution (histogram/KDE), DSCR by year (bar chart), and a scenario comparison (horizontal bar chart). One sidebar with a scenario dropdown that updates the charts. Tech stack: Python, Streamlit, Plotly, numpy. No database, no authentication, no deployment needed. Desktop only. Data: I will provide a .npz file with pre-computed numpy arrays (IRR distributions, DSCR arrays, scenario values). I will give you the exact key names and shapes. You j...

I have a raw set of patient records and want to turn it into a functional medicine-recommendation engine built in Python. The system should read symptom text typed by a user, run it through a pre-trained machine-learning model, and return a ranked list of suitable medications. Scope and key tasks • Data pipeline: remove duplicate records and normalise numeric or categorical values so every observation is model-ready. • Feature selection & training: experiment with at least Random Forest and Logistic Regression; pick the best model using accuracy, precision and recall. • Evaluation report: include confusion matrices and a short note explaining why the chosen model performs best. • Lightweight dashboard: a simple Flask or Streamlit interface with one free-tex...

- Developed ChurnShield, an end-to-end AI-powered platform for customer churn prediction and retention intelligence, utilizing Python, FastAPI, TensorFlow, and Streamlit. - Created a custom Artificial Neural Network (ANN) featuring three dense layers, batch normalization, dropout regularization, early stopping, and Adam optimization for churn prediction. - Implemented industry-specific machine learning pipelines for telecommunications and banking datasets, incorporating automated preprocessing and feature engineering. - Established intelligent churn risk classification systems that categorize customers into high, medium, and low-risk groups based on probability scoring. - Designed an interactive, cyberpunk-inspired analytics dashboard for real-time KPI monitoring, risk segmentation, cu...

• Built StockAI, a full-stack AI-powered stock market analysis and trading platform using Python, FastAPI, Streamlit, XGBoost, and Machine Learning. • Developed dual-machine learning models for stock price forecasting and BUY/SELL signal generation using 5 years of historical market data. • Engineered 35+ advanced technical indicators including RSI, MACD, Bollinger Bands, ATR, Stochastic Oscillator, Williams %R, OBV, moving averages, volatility metrics, and momentum-based features. • Implemented feature engineering pipelines to transform raw OHLCV market data into predictive trading intelligence. • Built time-series forecasting systems with proper train-test separation, walk-forward validation, and backtesting to eliminate data leakage. • Created confiden...