Computer science
Resume examples

Evaluated technology requirements to accurately and efficiently analyze data, revamped out-of-date systems, and reduced technology costs throughout the company. Developed and supported multiple databases and provided high-level technical support to clients.

• Managed the development team, introduced project management best practices, and established formal project planning and scoping processes
• Improved analytical accuracy from 92% to 97% within 6 months through rigorous development and implementation of new processes and procedures.
• Saved the company $300K by designing and implementing in-house data analytics governance, change management, and training scheduling systems.
• Optimized resources by outsourcing data backup and initiating the company’s first off-site backup for data.
• Co-introduced and championed improved methods for data visualization as a cost-effective solution to present findings to clients.

Led 10-person team devising ingenious solutions to complex problems such as big data, business intelligence, and data analytics. Created partnerships with Cloudera, Datastax, and Ne04J.

• Patented three breakthrough methodologies that generated $7 million annually.
• Data Partitioning and Indexing (DPI): speeds up calculation and simplifies range-interval queries for data analytics.
• Compressed Data Warehouse (CDW): slashed server space, boosted efficiency, and accelerated querying.
• Automated Online Advertising System (OAS): applied game theory to calculate payments to inventory partners.
• Provided consulting services to C-Level executives for big data strategy, platform selection, reference architecture, ROI modeling, an enterprise data hub, real-time analytics, visualization, and migration to the cloud. Built a development team with combined subject-matter expertise in architecture and optimization for three areas of programmatic advertising:
• Advanced the state-of-the-art patented methodologies and algorithms —for automatic buying and selling of online ad impressions via real-time auctions that occur as fast as a webpage can load.
• Re-architected DMP and DSP platforms for a major ad-tech firm — converted to a real-time, in-memory platform.
• Built prescriptive architecture to run large production clusters for spot-market AWS instances.
• Architected cloud Infrastructure and massive data migration —from an on-premise data center to the public cloud— for the Washington Healthcare System.

Leveraged machine learning and deep learning expertise in developing analytics solutions for pattern recognition in large data sets. Coordinated the design, development, and implementation of predictive models and forward-thinking algorithms which optimized value extraction from data sets.

• Led the data science team in developing and enhancing several models using problem resolution and process optimization algorithms.
• Conceptualized, developed, and rolled out innovative tools that improved the analysis of unstructured data.
• Directed numerous machine learning algorithm projects, writing tests to handle unforeseen errors effectively.

Recruited to oversee data science division and implement new project management policies and procedures. Managed the software development and engineering teams and implemented best practices to encourage efficient communication with other company divisions, including business and finance.

• Established project management fundamentals that improve customer satisfaction ratings and project acceptance levels.
• Led team that improved the RFP response process for new data science projects by 75%, leading to an elevated number of contracts per quarter.
• Improved analysis turnaround cycle by 50% by streamlining quality control procedures for all data science activities.
• Implemented AI/ML algorithms with the ability to run on structured data across several large-scale cloud data environments.
• Developed and reviewed reproducible code from team members to integrate and standardize disparate datasets.