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Charlie
charlie.isaksson@gmail.com
214-909-0842
Plano, TX 75025
Data Scientist and ML Engineer - Data Streaming
16 years experience W2
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Summary

Experience
Principal Machine Learning Engineer
Information Technology
Jul 2019 - present

Consultant : Data Scientist and ML engineer

Charlie Isaksson is an enthusiastic contributor who loves to learn and contribute to the team. With more than 10 years of industry experience in Software Engineering and Data Science. Charlie is currently serving as a Principal Machine Learning Engineer at phData where he is implementing best practices in machine learning engineering methodologies such as ETL technologies, data analysis, big data technologies, data management, predictive and exploratory model development, and data visualization. Has proven success in the field of Machine Learning. For instance: Lead multiple machine learning projects, that include designing and developing large-scale machine learning models and open source software. Most recently, designed and implemented a deep learning framework that addresses many issues related to image model training, specifically: Multi-network architectures, Different versions of optimizers, Utilizing any number of GPUs, Multi-Interface (Tensorflow, Slim, Keras), Feature Extraction, Transfer Learning, Visualization, Automation of model validation and Nvidia-docker deployment Published numerous papers in the field of Data Mining and recently implemented DenseNet using Slim interface. Developed an end to end data pipeline, ingestion, and aggregation of data and model development leveraging spark on Cloudera’s infrastructure. Automated the ML model and data by utilizing Oozie workflow Used various interactive visualization techniques to provide the customer with valuable insight into their large data. Charlie has experience in a broad range of tools and programming languages, such as R, Python, Hadoop, SQL, Hive, and Tensorflow. Specifically: Languages/Tools: C, C++, Java, Scala, Python, iPython Notebook/Jupyter. Exploratory: Clustering, text mining and association rules, Predictive: Markov model, k-nearest neighbor, support vector machine, XGBoost, convolutional neural networks, regression, and text classification, Database: DB2, Oracle

C C++ DB2 Docker Containers ETL Java Oracle Python Software Engineer SQL Clustering Big Data Data Mining Data Science Data Visualization Hadoop Hive Scala Spark
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Data Scientist
Apr 2018 - Dec 2019
Richardson, TX
As a key Data scientist and project lead. Project domains include text mining, data mining, deep learning, and numerous cost-savings initiatives.
Data Mining
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Principal Data Scientist
Feb 2019 - Jul 2019
Addison, TX
  • Utilize deep learning technique to detecting homoglyph attacks by converting text domain names to images
  • Optimized threat model for automated detection of cyber threats, including indicator of compromise and email spam.
  • Advance machine learning techniques to address large-scale security analytics challenges, such as extremely imbalanced datasets, concept drift, and near real
  • time model updates.
Machine Learning
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Lead Machine Learning Engineer
Aug 2016 - Apr 2018
Richardson, TX
. Collaborated with Data Scientists and other analysts on the advanced analytics teams to help them design, develop, implement and test Hadoop applications for the collection and integration of analytic data. . Drove application and data architecture direction for analytics. . Developed spark applications to call analytical models from spark and automated the data ingestion from different data sources, such as: DB2, Hive, PostgreSQL and performed complex data aggregation within the data pipeline. All using spark, python and Scala. . Integrated new data sources with existing analytics infrastructure by defining requirements and represented the analytical needs of the research department. . Individual contributor on a project to classify vehicle damage. Designed, developed, and implemented a deep learning framework that addresses many issues related to image model training, specifically: multi-network architectures, different versions of optimizers, utilizing any number of GPUs, multi-interface (Tensorflow, Slim, Keras), feature extraction, transfer learning, visualization, automation of model validation and Nvidia-docker deployment. .2017 Q2 received Special Achievement Award for delivering a model into StateFarm production system on an extremely aggressive time frame.
DB2 Docker Containers PostgreSQL Python
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Data Scientist at CTO Office
Jan 2015 - Aug 2016
Plano, IA
  • As a key data scientist, I worked in a multidisciplinary team on a strategic automation initiative that spanned the full data product lifecycle from all the way of vague idea to scalable proof-of-concept product.
  • I advanced this anomaly detection project out of the concept inception phase by automating the data retrieval from one of the largest telecom provider, and performed difficult data cleansing and aggregation all in python.
  • I was involved in presenting the client with different visualizations of outliers to clarify the problem & highlight possible solutions.
  • Using Python and R, I applied various time series forecasting methods such as seasonal/trend decomposition, ARIMA modeling, & exponential smoothing to analyze millions of performance management metrics
  • After researching various techniques such as Principal Component Analysis and clustering to find the best detector, I presented results to team & client using IPython notebooks
  • I then worked with the team to scale our selected detector to production data volumes on a true cluster of nodes using oozie, Spark SQL, PySpark, SparkR
Data Cleansing Oozie Spark SQL
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Principal Software Engineer
Jul 2010 - Jan 2015
Plano, IA
I was one of key developer in the new GeoProbe product (GeoBlade). I have delivered numerous innovative solutions on an extremely aggressive schedule to save $30M annually. Worked in team to dramatically improved product usability, performance, and robustness, which resulted in major gains of customer satisfaction level. Delivered a large number of complex projects within market-leading GeoProbe Monitoring Solution for wireless and landline networks. Built up and refined advanced skill set in C++, Python, UNIX, Linux, Solaris, Java, build systems, computer networking, distributed systems, high concurrency, real-time systems, performance optimization, advanced debugging techniques, Oracle, telecommunications protocols, and many other areas.
C++ Java Linux Oracle Python Software Engineer Solaris UNIX
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Teaching Assistant
Aug 2007 - Jul 2010
Teaching C++, Java and web courses.
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IT/LAN specialist I
Nov 2006 - Aug 2007
· Apply Problem Solving techniques · Apply knowledge of Novell IT related Services · Use methodologies for Linux/UNIX Server, Windows Server 2000 and 2003, MacOS Server · Advice in selecting the appropriate architecture for the solution that provides the necessary structure to the design and allows for future growth · System Administrator for Windows Server 2000 and 2003 · System Administrator for SUSE Linux Enterprise Server · Administrating for VMware Server and VMware ESXi · Administrating Norton Ghost Image Server · Administrating Faronics Deep Freeze Server · Manage software installation and upgrades
LAN UNIX Windows
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Technical Support Specialist
May 2005 - Nov 2006
· Support dedicated Internet customers · Troubleshoot connectivity issue on individual customer circuits · Support Fiber, wireless, copper wire, video and voice · Maintain efficient communication operations, SW loop testing software · Submit and resolve business customer's request
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Edit Skills
Non-cloudteam Skill
Education
Data Mining
Southern Methodist University, 2007 - 2016
Computer Science
Mid Sweden University, 2002 - 2005
Skills
Python
2021
8
C++
2021
6
Java
2021
6
Oracle
2021
6
Software Engineer
2021
6
UNIX
2015
6
Linux
2015
5
Solaris
2015
5
DB2
2021
3
Docker Containers
2021
3
Data Mining
2021
2
PostgreSQL
2018
2
Spark
2021
2
SQL
2021
2
Big Data
2021
1
C
2021
1
Clustering
2021
1
Data Cleansing
2016
1
Data Science
2021
1
Data Visualization
2021
1
ETL
2021
1
Hadoop
2021
1
Hive
2021
1
LAN
2007
1
Oozie
2016
1
Scala
2021
1
Windows
2007
1
Apache
0
1
C#
0
1
DHCP
0
1
DNS
0
1
HTML
0
1
in-memory databases
0
1
Machine Learning
2019
1
mSQL
0
1
MySQL
0
1
NCR
0
1
NetScout
0
1
Perl
0
1
PHP
0
1
RHadoop
0
1
Scripting
0
1
SCSS
0
1
Spring
0
1
TCP/IP
0
1
UML
0
1
Visual Studio
0
1
XML
0
1
Publications
SOStream: Self Organizing Density-Based Clustering over Data Stream
Springer-Verlag Berlin Heidelberg, 2012
A Comparative Study of Outlier Detection Algorithms
Springer Berlin Heidelberg, 2009
Risk Leveling of Network Traffic Anomalies
IJCSNS International Journal of Computer Science and Network Sec, 2006