Machine Data

Suraj Didwania

Sunnyvale,CA • 312-***-**** • **************@*****.***

GitHub: github.com/surajdidwania LinkedIn: linkedin.com/in/surajdidwania SUMMARY: Data Scientist with 3 years’ experience with machine learning skills, productionization and business knowledge to deliver scalable and efficient data science products.

PROFESSIONAL SKILLS

Programming Languages: Python, Java, Spark, SQL, NoSQL (MongoDB) Tools: AWS, Google Cloud, Git, Docker, Kubernetes, Airflow, Tableau, Microservices Machine Learning: Supervised & unsupervised learning, Time Series, Deep learning, Forecasting, Bayesian Learning, MCMC, Gaussian Process, Reinforcement Learning(Multi-Armed Bandits), A/B Testing, Hypothesis Testing, Distributions, Regression Framework and Libraries: PyTorch, TensorFlow, Keras, Pandas, Numpy, Scikit-Learn, Matplotlib EXPERIENCE

Data Scientist, SOC Telemed Jan 2019- Present

• Extreme event forecasting for operations in Telemedicine: o Lead development and productionization of Deep and Confident prediction for patients demand using Bayesian deep prediction model using automatic feature extractor in Tensorflow achieving a 30% more accurate prediction of performance than previous years.

o Worked on statistical modelling and analyzing large scale data with focus on Operations. Developed Time Series Machine Learning Model(SARIMAX + LSTM) in Python for solving the Demand of Physicians with end-to-end data infrastructure.

• Reinforcement Learning for best performing state: o Machine learning algorithms for Multi-Armed Bandit problem for identification of best performing state for telemedicine which provides maximum profitability.

• Bleed rate classification for Neuro patients using clinical data: o Working on hierarchical multi-modal classification to perform two step prediction. XGBoost, SVM and Adaboost Model involves predicting if patients given tPA will bleed or not achieved an accuracy on test dataset of 81% with precision 0.72. o Utilized natural language processing (NLP) to uncover insights from doctor’s prescriptions.

• Implemented automated anomaly detection of hospitals Neuro and Psych demand using isolation forest to identify unusual volume achieving 20% SLA improvement during COVID. Machine Learning Engineer, Yantriks LLC Aug 2018 – Dec 2018

• Implemented ATP Recommendation Engine with Tensor Flow and Cloud Machine Learning Engine in Google Cloud Platform

(GCP). Extracted 1TB data from Google Bigquery to GCS to perform data cleaning

• Machine Learning (Anomaly Detection) for Nginix Logs- Identifying Operational Issues in the website.

• Multidimensional Time Series Analysis for performance metric of API calls using LSTM and GRU in TensorFlow. Machine Learning Intern/Co-op, JCPenney Inc. May 2017- May 2018

• Multi-dimensional Recurrent neural network (LSTM) to process large scale time series data. POC in Keras and deployment in Tensorflow. Statistics and Bayesian methods such as Monte Carlo Markov Chain achieved SMAPE of 12%.

• Implemented machine learning classifier models(Random Forest, XG Boost, Logistic Regression) for Control & Treatment set if digital advertisements would impact customers. Achieved maximum precision of 0.80 PROJECTS

Google Landmark Recognition 2019

To recognize which landmarks (if any) are depicted in images. 4.1M images dataset landmark recognition using ensemble resnet model. Data Engineering in GCP, Model building ResNet using PyTorch and Model Evaluation. CNN, PyTorch, Python, GCP and GPU. Tera Sorting implementation using Shared Memory, Priority queue, Hadoop and Spark Sorting of 1TB and 128GB of data by implementing native algorithms using disk throughput and threads, message passing interface technique, Hadoop using Amazon EC2. Testing, evaluation and comparison of all the four techniques mentioned above. RESEARCH PUBLICATIONS

International Stroke Conference(ISC) 2021 Publication on The Effects of COVID-19 On Telestroke Care Delivery August 2020 International Stroke Conference(ISC) 2021 Publication on Sex Differences In the Delivery of Acute Telestroke Care August 2020 EDUCATION

Master of Science in Computer Science, Illinois Institute of Technology, Chicago, IL-USA; GPA:3.90/4.00 2016 - 2018 Bachelor of Technology in Computer Science, SRM University, India; GPA: 3.5/4.0 2010 – 2014

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