Ph.D. Machine Learning and IoT Engineer

Description

We’re representing an accomplished data analytics and internet of things specialist with 10+ years of experience. They’re passively exploring opportunities at early-stage startups.

Highlights

  • Architected, designed, and developed a metadata-driven IoT system for a smart city with the ingestion rate of 10K events per second from 100K sensors in multiple domains. Leveraged Elastic Search, PostgreSQL, and TimescaleDB to manage multiple demands on a Big Data platform using an innovating and extensible Data-Model architecture
  • Developed analytical solutions and machine learning algorithms such as decision-tree classifiers and regression to address the low-throughput region in a mobile access network
  • Built multi-tier server architecture including Analytics, Database, and UI/Visualization tiers to implement multi-service architecture for a full-stack development

Education

  • PhD. in Electrical Engineering
  • MS in Computer Engineering
  • BS in Computer Engineering

Technical Skills

  • Big Data Solutions including SQL and NoSQL on MS SQL, PostgreSQL, Teradata, Netezza, and Apache Spark for advanced analytical applications with an applied MapReduce programming model
  • Machine Learning and Deep Learning Algorithms mainly logistic regression, decision tree, associative learning, topic modeling with LDA and k-means clustering, k-NN, CNN and LSTM
  • Time Series Forecasting using ARIMA Model and LSTM in Python and R
  • Image Processing: NumPy, scikit-image, SciPy, Pillow, OpenCV, YOLO, Pose Detection
  • Programming languages Python, R, Java, JavaScript, AngularJS, Shell Scripting, HTML, and CSS
  • Data Visualisation: D3.js, DC.js and R-Shiny, Tableau, Power BI
  • DevOps: CD/CI Automation, GIT version control, GitHub Enterprise, Bitbucket, Ansible, Jira
  • Mathematical Modeling, Advanced Analytics, and Statistics
  • Network Knowledge: Protocols (HTTP(s), TCP/IP, SCTP, SNMP, SSH), Mobile (5G, LTE, UMTS)