Expertise to obtain knowledge and insight from data through predictive, descriptive, and prescriptive analytics.

Specialize in understanding the data being used for analytics to obtain the highest quality data set for the most accurate results, such as feature engineering.

Optimize business intelligence for innovative strategies to maintain a competitive advantage, increase revenue, and retain customers.

I have expertise with all aspects of Microsoft Office 365 and Excel 2016 with special emphasis on using pivot tables for data analytics.

My focus is to harness the underutilized, yet powerful analytical capabilities of Excel to assist clients through optimized business intelligence.

The most important algorithms for data analysis are categorized as classification, clustering, statistical learning, association analysis, link mining, bagging & boosting, sequential patterns, integrated mining, rough sets, and graph mining.

The Python language is ideal for data science and analytics through scientific, mathematical, machine learning, statistics, and visualization packages.

Google, Microsoft, Amazon, and Oracle offer cloud-based services for big data and analytics with built-in features along with drag-and-drop interfaces for business intelligence and machine learning.

My data analytics expertise includes how best to utilize these features and benefits.

The Apache Hadoop framework for processing large data sets consists of MapReduce, YARN, and HDFS supported by services such as Spark, Pig, Mahout, and Hive.

Database administration and configuration for MySQL, PostgreSQL, LAMP (Linux-Apache-MySQL-PHP), Apple FileMaker, JSON web services, Java, JDBC, and Oracle.

Law practice management software is used to manage the life cycle of a legal matter through technology. This includes client/matter management; legal calendaring and tasks; contacts and business development; email and phone call management; document management; document automation; knowledge management; time and expenses; billing, collections, and trust; accounting integration; and conflict checks.

eDiscovery refers to the review and production of digital files. These digital documents are imported into a review platform for analysis. The Electronic Discovery Reference Model (EDRM) consists of multiple stages: identification, preservation, collection, processing, review, and production.

My background in software and hardware is ideal for developing comprehensive security strategies and reduce the impact of cyber risk.

Emphasis on an overall information security framework by taking an inventory of all computers, devices, and software; verifying secure configurations; vulnerability assessments; and malware defense.

Certified system administrator for Mac OS X and Linux.

Registered developer for iOS, Android, Mac OS X, and Windows.

Commercial and personal experience with Java, Objective-C, Swift, Ruby on Rails, Python, JSON, XML, PHP, HTML, CSS, JavaScript, C, C++, Perl, and Assembly Language.

Expertise in agile software development techniques and the scrum framework (sprint planning, daily scrum, sprint review, and sprint retrospective).

Quality assurance and software testing to find problems in code and determine what is missing while simulating real-world scenarios to analyze functionality.