Vikram Narayan
Product Manager, AI Ops at Cisco Meraki
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolVikram Narayan is a product leader and former engineer with 11 years of experience turning data-driven insights into customer-focused products across fintech, civic tech, and B2B SaaS. Currently building an AI Ops assistant at Cisco Meraki to proactively optimize and self-heal Wi‑Fi, he previously drove millions in ARR and company-wide roadmap strategy at StreamNative, including launching their flagship conference. His engineering roots (Quantopian, Zipline, pyfolio) inform a rigorous approach to product decisions—he’s contributed performance attribution and core trading models to well-known open-source finance projects. Vikram excels at aligning exec vision with engineering execution, cutting onboarding time through automation and tightening feature prioritization around ideal customer profiles. He blends technical depth in backend systems and analytics with strong UX and cross-functional leadership, and is especially adept at turning complex domain expertise into simple, testable product features. Based in Boston, he favors measurable outcomes and practical automation over speculative roadmaps.
11 years of coding experience
9 years of employment as a software developer
Bachelor's Degree, Computer Science and Government Double Major, Bachelor's Degree, Computer Science and Government Double Major at Dartmouth CollegeGraduation Speaker, Graduation Speaker at Corona del Sol High School
Spanish, Tamil
Github Skills (8)
finance10
pandas10
code-optimization10
zipline10
python10
algorithmic-trading10
testing10
dependency-management9
Programming languages (6)
Github contributions (5)
quantopian/trading_calendars
Jun 2018 - Oct 2018
Calendars for various securities exchanges.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 48 commits, 18 PRs in 4 months
Contributions summary:Vikram's commits focused on refactoring and improving the `zipline/errors.py` and `zipline/utils/memoize.py` files within the `trading_calendars` repository. They removed unnecessary errors and added the `lazyval` decorator for attribute memoization. These changes indicate a focus on code optimization and maintainability, likely to improve the performance and robustness of the codebase. Furthermore, the user added modules and stole things from zipline, suggesting they were working on dependency management and reusing code from another repository.
calendarscalendarexchangessecurities
quantopian/pyfolio
Aug 2017 - Jun 2018
Portfolio and risk analytics in Python
Role in this project:Data Scientist
Data ScientistContributions:92 commits, 56 PRs, 24 pushes in 9 months
Contributions summary:Vikram significantly enhanced the `pyfolio` library by implementing performance attribution and related functionalities. They added a comprehensive performance attribution feature, including a summary table and plots, indicating a strong focus on portfolio analytics. The user also optimized existing code, fixed inputs, and updated documentation, demonstrating a commitment to code quality and maintainability. Furthermore, the user integrated testing, including test cases for performance attribution, to ensure the correctness of their contributions.
riskanalyticspython
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