Vahab M.

Summary:

I'm a data scientist experienced in building statistical models, algorithm design, and causal inference. I can apply my knowledge and skill set in any application with analytical frameworks and big data. My most recent full-time jobs have been focused on:

1. quantitative anomaly detection in the Medicare/Medicaid big data to uncover fraudulent activities by bad actors (hospitals or healthcare systems)
2. experiment design and causal inference to optimize the budget in various online and offline marketing channels. Also, developing Machine Learning algorithms to study both sides of the job market in order to have a more tailored advertising campaigns for job seekers and employers to improve various engagement metrics.

I also have around 7 years of teaching experience in Mathematics & Physics. I'm really good at understanding stakeholders' real needs and also in presenting quantitative analyses to people with no or minimal technical background.

Key Qualifications

Programming:

• Proficient in R, Python, SQL, and familiar with Java, and Object Oriented Programming.
  Developing Algorithms:
• Searching and Clustering Algorithms in Graphs, Pattern Recognition, Computer Simulations, and Machine Learning Algorithms such as K-means, K-NN, SVM, Decision Tree, Random Forest, Neural Networks, etc.
  Statistics:
• Matching Methods, Panel Data, Time Series Analysis, Experiment Design and Causal Inference.