palantir-technologies > palantir-technologies Employee Directory > Alexander Egorenkov
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Alexander Egorenkov
Software Engineer
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Location: New York City Metropolitan AreaApprox. Years of Experience: 13
Alexander Egorenkov's Current Workplace
Palantir Technologies
Company Size
2500+
Amount Raised
$3.0B
At Palantir (NYSE: PLTR), we're helping the world's most important institutions use their data to solve their most urgent problems. Our software lets our customers integrate and analyze all of their data so they can answer questions that they couldn't before. From delivering disaster relief to building safer automobiles, we're honored to help make our partners better at their most important work. \n\nTogether with our customers, we're building the future of national security, healthcare, energy, finance, manufacturing, and more. And we need bright minds from around the world to help us.
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Notable Investors
Founders Fund, Fujitsu, ARK Investment Management, Ethos VC, Bracket Capital
GovTech
Big Data
Consulting
Data Mining
Data Integration
Data Visualization
Intelligent Systems
Cloud Data Services
Enterprise Software
Predictive Analytics
Business Intelligence
Professional Services
Experience
Software Engineer
Palantir Technologies
Nov 2018 - Present
6 yrs 6 mos
Software Engineer
Codesmith
2018 - Sep 2018
9 mos
• Developed React/Redux/Node SPA with code reuse from existing online learning platform. • Produced reusable React component library which decouples layout, component, and content populated from parsed YAML to act as a cms allowing other teams to update content. • Leveraged CSS modules to create reusable UI styled components for increased modularity. • Designed a DSL to express Redux logic and generate reducers to reduce engineering time. • Implemented an interpreter to parse a domain specific language and perform immutable updates on Redux state. • Implemented a Depth First Search algorithm to infer update locations in arbitrary Redux state-trees. • Wrote Integration and Unit tests to enable rapid language redesign while maintaining code and API correctness.
Research Team
Resources for the Future
Jun 2013 - Mar 2018
4 yrs 10 mos
• Designed a denormalized HStore schema in PostgreSQL to reduce a 50k row indexed write query latency by 90%. • Utilized Haproxy, NGINX, and Vagrant to implement session-based load balancing for a virtual machine application layer on multiple cloud hosts and development environments, ensuring high availability. • Implemented a hotfix for OpenLayers.js caused by a Google Maps update preventing weeks of frontend down-time. • Employed a MCP numerical optimization algorithm for an electricity market model distributed across commodity hardware to reduce around-the-clock runtime from several weeks to a few hours per run, ~99%. • Architected a design that decouples MCP model and scaling code to save ~20% of team engineering time.
General Assembly
Aug 2015 - Oct 2017
Lead Data Science Instructor
Jul 2016 - Oct 2017
1 yr 4 mos
• Taught the first pilot Data Fundamentals course for Booz Allen Hamilton and served as a key member in its design. The pilot was accepted and will train 5,000 data professionals. • Managed 300 hours of workshop-style classroom time including lecturing, live coding, and in-class troubleshooting of student code and git workflows. • Achieved a top-ranking Net Promoter Score of 71 in my latest part-time class. • Provided technical mentorship on ~100 10-week data science projects through code review and project scoping.
Subject Matter Expert: Data Scientist
Apr 2017 - May 2017
2 mos
• Developed Python Machine Learning code and Jupyter Notebooks in close collaboration with a Data Science team to ensure technical clarity and correctness of concepts across ~100 GitHub Enterprise repositories for a global audience. • Improved the Data Science Immersive curriculum covering Python, data manipulation, databases, supervised learning, clustering, dimensionality reduction, and introductions to deep learning.
Associate Instructor (Data Science)
Aug 2015 - Aug 2016
1 yr 1 mo
Associate Instructor for General Assembly's 11-week Data Science course.
Machine Learning/Text Classification, Python
Data School
Feb 2016 - Mar 2017
1 yr 2 mos
Teaching Assistant for Machine Learning with Text in Python for several class sessions. Responsibilities include clarifying advanced programming and machine learning topics on student's in-class and real world projects and providing code review for student homework.
Independent Contractor
FEEM - Fondazione Eni Enrico Mattei
Jun 2013 - Sep 2013
4 mos
• Data wrangling and exploration on a home energy efficiency survey based in Italy.
Statistical Modeling and Analysis, Survey Design
University of Maryland Department of Agricultural and Resources
Feb 2012 - May 2013
1 yr 4 mos
• Survey design • Econometric modeling • Data wrangling
Research Intern
Maryland Sea Grant
Sep 2012 - Dec 2012
4 mos
• Analyzed a needs assesment and compiled a report of findings
Education
  • 2012 - 2013
    University of MarylandMathematics
  • 2010 - 2012
    University of MarylandBachelor's Degree, Economics, Statistics Minor
  • 2008 - 2010
    Montgomery CollegeAssociate's Degree, Business Administration and Management, General