Apella is a technology company for better surgery. We use artificial intelligence, computer vision, and modern communications to improve the most critical aspect of healthcare.

• Lead team of 3 software engineers from Operations/Data Quality in the design, development, and maintenance of a suite of in-house data management applications
• Achieve 80%+ reduction of manual data patching requests, boost customer success team efficiency, reduce human errors and third-party vendor dependency
• Identify technical debts and allocate regular development time for repayment, increase test coverage throughout the code base
• Provide comprehensive technical documentations and architecture diagrams, adopt best practices and highly automated workflow to increase productivity, mentor new junior developers

• Participated in the design, implementation, and maintenance of next-gen metadata-driven Human Capital Management platform using highly scalable Node.js microservices
• Transformed legacy monolithic libraries into AWS-powered microservices that perform compilation, validation, and resolution of metadata documents, serving millions of requests per day
• Contributed to Lifion's data migration effort (Couchbase to AWS Databases) which saved the company more than $75,000 in licensing cost
• Implemented code instrumentation to monitor service health and measure performance using tools such as Kibana, DataDog, and HoneyComb, improving overall system reliability and reducing debugging time
• Organized Lunch and Learn sessions to share knowledge among team members, made contribution towards the larger organization with "Lifion 5% time", mentored co-ops on technical projects

• Played a key role (first full-time employee) in building out the firm research infrastructure and its transition from a boutique research startup to an established hedge fund managing over $1 billion
• Compiled real-time market analytical data and provided charting framework (in R) to support research findings and publications
• Designed, developed, and maintained the Risk and Order Management System, Value at Risk monitor and other applications (Excel/VBA/Bloomberg)

• Implemented mean-reversion and momentum statistical arbitrage strategies across equities, futures, and FX markets (MATLAB/R)
• Performed back-testing analysis with transaction costs, extended execution assumptions with time-varying adaptive buy/sell signals

• Developed Perl scripts to analyze and report the firm’s automated trading system performance