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    Bahar Sharafi

    Data Scientist at Nike

    Bahar Sharafi is a data scientist specializing in computational and experimental biomechanics with experience in applying time-series methods, anomaly detection, and regression techniques to extract business insights.

    Currently, Bahar works at OSRAM where she focuses on analyzing various sensor data, from urban farming to after market sales, to drive business decisions by using tools like Python, SQL, R, and MATLAB.

    Bahar's programming skills include Python libraries like Scikit-learn, Pandas, NumPy, SciPy, StatsModels, and Keras, as well as SQL (PostgreSQL), R (DPLYR, R Shiny), and MATLAB. She is well-versed in techniques such as regression, decision trees, random forest, time series analysis, LSTM, ARIMA forecasting, PCA, neural networks, clustering, anomaly detection, and more.

    Her educational background includes a Doctor of Philosophy (Ph.D.) in Mechanical Engineering from the University of Virginia and a Bachelor of Science (B.S.) in Mechanical Engineering from Sharif University of Technology.

    Bahar has previously worked at organizations like Nike, Celect, Inc., and Insight Data Science, bringing her expertise in data science to various fields. She has also held positions as a Research Scientist at Liberty Mutual Insurance, a Postdoctoral Research Fellow at Northwestern University and the Rehabilitation Institute of Chicago, and a Graduate Research Assistant at the University of Virginia, among others.

    With a comprehensive background in both academia and industry, Bahar Sharafi is adept at applying advanced data science techniques to solve complex problems and drive business growth.

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    Location

    Greater Boston