Data Scientist/machine Learning Engineer Resume
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Santa Clara, CA
SUMMARY:
- Data Scientist/Machine Learning Engineer with 10+ years of industry experience
- Develop and deploy machine learning models based on Artificial Neural Networks, Principal Components Analysis, Random Forest, Gradient Boosti ng, Partial Least Squares, k - means Clustering. Applications include Time Series Forecasting, anomaly detection, computer vision, sequence modeling, topic classification, sentiment analysis, Recommendation Engines, real-time process control/optimization.
TECHNICAL SKILLS:
Programming Languages/Packages: Python, R, Matlab, Keras, TensorFlow, Scikit, Numpy, Pandas, Matplotlib and Seaborn, Natural Language Tool Kit, Apache Spark, Hive, NoSQL
WORK EXPERIENCE:
Data Scientist/Machine Learning Engineer
Confidential, Santa Clara, CA
Responsibilities:
- Object identification and logo recognition in household images (AWS Marketplace model packages: GluonCV YOLOv3 and Sensifai)
- Automated parsing of PDF forms to extract key-value pairs/Named Entity Recognition (AWS Textract, Spacy)
- Call volume forecasting for customer service center (LSTM Sequence to sequence); Monitor news stories and associated sentiment to predict impact of external events (data breaches, natural calamities, etc.) on call volume to optimize call routing, resource scheduling and prepare response strategy
- Topic clustering/classification and sentiment analysis to summarize and obtain actionable insights into customer complaints/reviews (LDA2Vec, Natural Language Toolkit, Spacy)
- Real-time anomalous topic detection based on call/chat transcripts (LSTM)
- Recommendation engine for prediction of customer problems and possible solutions based on customer’s geo-demographic data and interaction history (Random Forest, Gradient Boosting)
Applications Engineer
Confidential, Methuen, MA
Responsibilities:
- Convolutional Neural Network model to predict the physiochemical properties of gasoline from hyper-spectral images
- Deep Reinforcement Learning to determine optimal control trajectory in closed loop sequential control for cost minimization
- Design of Experiments based on Latin Hypercube sampling to generate data and train a simulated model of the environment for Reinforcement Learning model
- Hyper-parameter search using Bayesian optimization
- Significant contribution towards the growth/success of a successful startup company (revenue realization to increase in revenue up before acquisition by Confidential )
Applications Scientist
Confidential, Woburn, MA
Responsibilities:
- Principal Components Regression and Partial Least Squares Regression to predict physical properties of oil and natural gas samples in real-time (PCR, PLSR)
- Confidential model for high-altitude aerial monitoring to detect and quantify natural gas pipeline leaks using images captured by a LIDAR/Tunable Diode Laser
- Weibull distribution fitting and Cox regression modeling of data collected from a ccelerated life tests, warranty/failure data (Reliability analysis, S urvival/Hazard R ate F unction)
- Interpret statistical methodologies and results to non-statisticians in a multidisciplinary research team/environment
Research Assistant
Confidential, Raleigh, NC
Responsibilities:
- Random Forest based model to classify gasoline samples into different octane ratings with high accuracy for compliance and reporting at retail sellers/distributors
- C lustering based sampling technique to address between-class and within-class imbalance to improve classification performance of Random Forest models in a highly imbalanced multi-class classification problem
- Cleaned and analyzed large and complex data sets
- Review, implement and modify statistical algorithms described in research papers or available under open source
Associate Software Engineer
Confidential
Responsibilities:
- Write and execute test case scenarios/scripts to validate business requirements for Siebel based customer relationship management application
- W rite test scripts for quality assurance of web based financial applications