Currently an Extern @BeReal.
Computer Science at Columbia, learning product work through a BeReal product management externship and early industry experience.
Portfolio of coursework, early work experience, and the BeReal product management externship, showing hands-on product thinking and technical learning.
Developed an AI-powered knowledge assistant using Python FastAPI and AWS Bedrock (Claude) with RAG-based semantic search that reduces intern onboarding time from 3 days to 10 seconds by aggregating fragmented documentation across Slack, wikis, and internal tools; Integrated Slack API and PhoneTool for real-time peer discovery and implemented upvoting algorithms to surface high-quality answers across intern cohorts
Led team development of an AI-driven fitness recommendation engine, designing ML pipelines for personalized nutrition and workout plan generation using classification/regression models trained on structured user input and real-time biometric signal data
Computer Science at Columbia, learning product work through a BeReal product management externship and early industry experience.
I am Imanga L, a sophomore studying Computer Science at Columbia University. I have some work experience and I'm exploring product work through the BeReal product management externship while I shape my early career direction.
Externships
BeReal Product Management Externship
BeReal.
Experience
Director of Technology, Full Stack Engineer
Care For All · June 2026 – Present
SEO EDGE Participant
SEO Career · June 2026 – Present
Volunteer Webmaster
STEM DRC Initiative · Feb 2018 – Present
Software Development Engineer Intern , CloudWatch
Amazon Web Services · May – August 2026
Education
Columbia University
Major: Computer Science; Minor: Theatre and Film & Media Studies · Class of 2029
Skills
Developed an AI-powered knowledge assistant using Python FastAPI and AWS Bedrock (Claude) with RAG-based semantic search that reduces intern onboarding time from 3 days to 10 seconds by aggregating fragmented documentation across Slack, wikis, and internal tools; Integrated Slack API and PhoneTool for real-time peer discovery and implemented upvoting algorithms to surface high-quality answers across intern cohorts
Led team development of an AI-driven fitness recommendation engine, designing ML pipelines for personalized nutrition and workout plan generation using classification/regression models trained on structured user input and real-time biometric signal data
✅ Verified by Extern · ⏱️ In progress
Discover how product teams at social apps like BeReal design for authenticity while driving user growth. In this externship, you’ll explore what keeps users coming back— benchmarking competitors, analyzing engagement features, and designing your own growth-driven app feature. You’ll learn how to balance product innovation with BeReal’s unique mission of real, unfiltered connection. Perfect for those interested in product management, UX strategy, or social media innovation, this experience gives you a hands-on look at how product teams grow platforms without losing their core values.
The externship examined how social apps balance authentic user experiences with growth objectives. The work compared competitor engagement features, analyzed tradeoffs between growth and authenticity, and produced a concept for a growth-driven feature tailored to BeReal's product constraints.
I translated research and comparative analysis into a concise feature concept and supporting artifacts, documenting competitive benchmarks and design tradeoffs that informed the proposed feature.
