Jessica Claire
  • , , 100 Montgomery St. 10th Floor
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  • Github : ag-inventor
Professional Summary

Results-oriented and innovative Senior Software Engineer with 5 years of experience. Easily communicates complex technical requirements to non-technical stakeholders. Excellent leadership record of leading development teams in enterprise-wide development projects.

  • Programming - Java, C, C#, Objective C, swift
  • Scripting - Python, ruby
  • Frameworks - Spark
  • Deployment - GCP, Cmake, jersey API, microservices
  • DB - TSDB, SQL, ElasticSearch, Solr
  • OS - Linux, Mac
  • IDEs - IntelliJ, Pycharm, CLion, Xcode
  • Unit Testing - jUnit, mock implementations
Work History
Sr Software Engineer (Title: Performance Engineer), 04/2020 to Current
Anthem, Inc.Springdale, AR,

Technical Stack: Java, Python, C, SQL, TSDB, typescript, Angular, java APIs, CUDA, Git, GCP

  • Directed AlertCorr project with 8-person team, incorporating event correlation and root cause analysis in NetDiagnostics (APM & Health tool).
  • Incorporated impact analysis in product to provide user with end-to-end analysis getting data from GCP, AWS, etc.
  • Added integrations with other tools like Splunk, NetVision.
  • Improved accuracy of Root Cause Analysis further to around 92%.
  • Used LSTM to do real time metric prediction. Using CUDA programming it was able to do predictions for 100000 metrics in 5-10 seconds.
  • Designing and implementing alerting mechanism in NetDiagnostics TSDB project in C which involves adding, removing, updating, aggregating and assessing over 10 million time series data stored in openTSDB(time series database) at every time interval (usually per minute).
  • Reviewed and incorporated latest technology innovations and development strategies to improve build speed, quality and end-user experience.
Senior Software Engineer/Consultant, 09/2019 to 03/2020
PanjivaVirtual, MI,

Technical Stack: Python, Spark, SQL, Git, GCP

  • Worked on anomaly detection module to get huge metric data and processing for anomaly detection on runtime using python, spark and deploying on Google Cloud. Used lightGBM and STM models. In runtime, precision and recall were 85% and 99% respectively
  • Worked on auto-scaling of resources by deciding how many servers need to be allocated based on past data and current trend using python, spark and deploying on GCP. Used combination of KNN and regression models and got accuracy of 90%
Software Engineer Team Lead, 09/2018 to 08/2019
Cavisson SystemsCity, STATE,

Technical Stack: Java, Python, C, SQL, TSDB, typescript, Angular, java APIs, CUDA, Git, GCP

  • AlertCorr - Designed and developed product based on Event correlation and root cause analysis which analyses alerts coming from NetDiagnostics(APM Tool) and detects correlation and diagnoses root cause. Use combination of algorithms for frequent pattern detection, anomaly detection and learning from past data. For many cases, it analyses over 10,000 time series and provides root cause at metric level in runtime with accuracy of 88%, while for another 6% cases it comes close to actual root cause. Used java, python, SQL, jerseyAPI.
  • Customer review analysis- sort bad user sessions from good ones using sentiment analysis. Designed and managed using Python
  • Log analysis - find anomalous logs in real time. Using pattern matching it will find out if current set of logs which are getting generated are anomaly and pointing to potential issue. Used combination of drain tree and LCS to identify log structures which is passed to RNN. In runtime it processes 200.000 logs per minute. Designed, developed and managed using Python
  • Created ML library for other products to include Machine learning in their domain. Designed and managed in java, python.
  • NetDiagnostics Dashboard Functionalities - designed and developed library for applying various functionalities such as seasonal prediction, anomalies, etc. in real time. Optimized to work on large data in real time
  • NetDiagnostics Alert and Anomaly Detection - singularly designed and developed optimized O(1) solution for theta prediction to get real time anomalies proactively on large time-series data
Software Developer, 06/2016 to 08/2018
Cavisson SystemsCity, STATE,

Technical Stack: Java, Objective C, Swift, C, C#, Linux, CUDA, Git, CVS, GCP

  • Built iOS framework to give support of product NetVision in iOS apps, which allows app developers to monitor and replay user experience
  • In-depth analysis and optimization of ELK kit to conduct faster indexing and search on big data. Added features and operations in data analysis in Java
  • Developed monitors to capture system metrics in real time and also created alerting mechanism based on these metrics in Java
  • Developed module which uses clustering to conduct analysis on set of flow-paths to identify patterns for performance analysis
  • Developed module for parameter prediction using Machine Learning to ascertain future problem that could occur. Precision and recall for this project was 95 and 99 percent respectively
Bachelor of Technology: Computer Engineering, Expected in 06/2016
Delhi Technological University - Delhi, India,
  • Completed Coursera course on Machine Learning

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Resume Overview

School Attended

  • Delhi Technological University

Job Titles Held:

  • Sr Software Engineer (Title: Performance Engineer)
  • Senior Software Engineer/Consultant
  • Software Engineer Team Lead
  • Software Developer


  • Bachelor of Technology

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