- 7+ years of experience with a transition from Network Analytics Engineer to Data Science Associate
- Domain Knowledge on IT Infrastructure products and Talent Assessment products
- Executed Network Infrastructure monitoring and Talent Assessment data - driven applications with proficiency in a fast-paced agile development environment to quickly analyze, develop and test potential use cases for the business.
- Proficient in Statistical Modeling and Machine Learning Techniques (Linear, Logistic, Decision Trees, Random Forest, SVM, K-Nearest Neighbors, K-Means, Bayesian and XG Boost) in Predictive Analytics, Segmentation methodologies, Regression based models, Hypothesis testing, PCA and Ensembles
- Expertise in transforming business requirements into analytical models, designing algorithms, building models, and reporting solutions that scale across massive volume of structured and unstructured data under guidance of Principal Data Scientist
- Hold regular meetings with product, user design, engineering and leadership teams to share new data and analysis.
Programming: Python, R, Java, C/C++
Data Analytics: NumPy, Theano, Pandas, SciPy
Machine Learning: Scikit-learn, Spark MLib, TensorFlow, PyTorch
Data Visualization: Matplotlib, Seaborn
Statistical Measures: Regression analysis, Hypothesis testing, ANOVA, Probability distributions, and Time-series analysis
Database: SQL, PostgreSQL
Networking: TCP/IP, SNMP, Switching and Routing
OS Platforms: Windows(Desktop/Server), Linux/Unix
Cloud Technologies: AWS, IBM Cloud, Build Tools - SVN, Git, Jenkins.
Other Tools: Jupyter, Spyder, Anaconda, VMware, JIRA, Wireshark, MIMIC
Confidential, Arlington, VA
Data Science Associate
- Designed, developed and deployed web application that implements the machine learning lifecycle from feature selection to cross validation
- Enhanced Talent Assessment products of the business through systematic research in NLP using various techniques.
- Created interactive and dynamic visualizations that generate valuable insights in data exploration and analysis phases
- Leveraged technologies like Python and R for parsing large volumes of structured and unstructured application and data
- Conduct advanced statistical analysis to illustrate statistical significance of experimental results and identify trends
- Developed improvements to experimental methods by analyzing machine learning model errors which increased employee retention rate by more than 50%
- Developed a pipeline to ingest, clean, aggregate, filter, and merge the stream of data from different datasets
- Interacted with various internal product groups to gather requirements for Data Analysis to provide insights and foster the adoption of Data Analytics in the new product development domain
- Extracted and transformed time series data and loaded the data into MySQL database through the Python interface and analyzed time series data in SQL using indexes and joins.
Network Analytics Engineer
- Optimized network performance by predicting and preventing crashes of network devices and identifying high - performance devices.
- Built a search capability and powerful machine leaning based information retrieval system to capture network infrastructure tendencies.
- Study whether network devices exhibit positive or negative behavior that can affect productivity or revenue.
- Identified similar failure devices in other networks when a crash happens in any network.
- Explored Base Rate statistics for platform crashes and software crashes.
- Explored comparisons across software versions with ANOVA statistical analysis.
- Transformed Data and performed statistical anomaly detection.
- Identified similar groupings of network devices by K-Means clustering accounting Dimensionality reduction, PCA and Encoding.
- Designed and implemented quantitative and qualitative research to provide insight and address network issues.
- Used SQL to extract actionable information from data.
- Developed and automated logistical data models to move data between IT systems.
- Conducted audits of outgoing alerts and identified discrepancies.
- Owned the design, development and maintenance of ongoing metrics, reports, analyses, dashboards, etc., to drive key business decisions and communicate key concepts.