Data/Machine Learning Scientist with a passion for solving complex business problems using data by designing, developing, and deploying predictive models using popular and state-of-the-art Machine Learning, Deep Learning, and Statistical Learning methods. Proven track record of delivering best-in-class solutions to complicated and ambiguous challenges in an agile development environment. CORE COMPETENCIES: ✔ Mobility analytics/ Population Intelligence ✔ Predictive analytics ✔ Geospatial Machine Learning (spatial analysis, geostatistics, kernal algorithms, kriging, monte carlo) ✔ Data Mining (data preparation, consolidation, imputation, transformation, interaction, modeling) ✔ Extract Transform Load (ETL) ✔ Supervised/Unsupervised Machine Learning ✔ Regression (Linear, Ridge, Neural Network, Lasso, Decision Trees, Random Forest, KNN, SVM etc) ✔ Classification (Logistic, Naive Bayes, KNN, Stochastic Gradient Descent, Decision Trees, SVM, etc) ✔ Clustering (k-means, hierarchical, DBSCAN, Gaussian Mixure Model, BIRCH) ✔ Deep Learning (CNN, RNN, LSTM, GAN, Neural Prophet) ✔ Time Series (ARIMA / ARIMAX, Recurrent Neural Networks, Auto Regressions) ✔ Bayesian Statistics (causal inference, probabilistic thinking) TECHNICAL SKILLS: Programming Languages: Python, SQL, NoSQL, PySpark, PowerShell, Bash, Conda, HTML, C, VBA Python Libraries: Numpy, pandas, Geospatial (GeoPandas, ArcPy, Folium, Gdal), Visualization (Matplotlib, Seaborn, Bokeh, Plotly), Statistical/Machine/Deep Learning (scikit-learn, SciPy, Keras, TensorFlow, PyTorch), Beautiful Soup, Regular Expressions. Cloud Technologies: Analytics Platforms (Azure ML Studio, Azure Cognitive Services, Azure Synapse Analytics), Warehouse Solutions (Azure Data Lakes), Azure IoT Hub, Visualization tools (MS Power BI, Tableau) Available to discuss new opportunities in Greater Sacramento Area, San Francisco Bay Area or virtual (remote), please contact me at vijaybendigeri@gmail.com.