Anisa Ahmed

Financial Planner • Project Manager • Product Manager • New York, NY, US

Product Development

Machine Learning

Financial Modeling

Software Engineering

Software Development

Project Management

Discrete Mathematics

Python

pandas

C Programming Language

Available for hire fromNegotiable

Full-Time Roles

Contracts

Recent Ivy League Engineering Graduate with a BS in Operations Research and Financial Engineering and a BA in Pure Mathematics and Economics

I am a recent graduate of Columbia University’s School of Engineering and Applied Sciences. Through Columbia’s dual bachelor’s degree program, I earned a BS in Operations Research and Financial Engineering from Columbia University (May 2024) and a BA in Pure Mathematics and Economics from Bard College (May 2022). My professional experience includes engineering trading simulation platforms at MathWorks and developing capital management solutions as a Summer Analyst at Citi. As a recent Kleiner Perkins Fellow at Codeium, I optimized AI-driven code tools to enhance developer efficiency across platforms. My passion for quantitative analysis and technical problem-solving drives my contributions in finance and technology.

Projects

Industrial Engineering and Operations Research Department, Senior Thesis (Honors)

Conducted extensive research (120-page thesis) on the Economic Theory of Pan-Africanism, employing statistical analysis, stochastic modeling, and optimization techniques to develop data-driven models and strategic recommendations for achieving sustainable growth and self-reliance in Africa.See More

Work History

KP Engineering Fellow, Codeium Software Engineering Intern

Kleiner Perkins, CodeiumInternJun 2024 - Aug 2024 • 3 mos● Engineered an autocomplete and chat product that efficiently supports daily active users, helping developers write code faster with fewer errors to ensure seamless developer experiences across multiple platforms and IDEs (Integrated Development Environments). ● Collaborated with senior leadership to develop “Codeium Live”, a real-time AI code assistant that delivers responsive and contextually relevant suggestions by integrating chat functionality directly within users' browsers for popular repositories. ● Designed and implemented an internal Kubernetes-native data processing framework, optimizing the handling of petabytes of data across thousands of spot CPUs, enhancing performance and scalability, and ensuring data processing efficiency. ● Developed a code attribution service that tracked the origin of code and verified it did not violate open-source or proprietary licenses to ensure compliance with licensing requirements, providing customers with assured compliance and robust intellectual property management. ● Developed and improved models for “Codeium Command”, focusing on instruction and edit capabilities, enhancing AI-driven code generation and editing. ● Optimized model inference performance using advanced techniques such as Nvidia CUTLASS, CUDA C++, and PTX assembly language, significantly improving computational efficiency. ● Developed features to enable remote parsing, embedding, and indexing of users' codebases, enabling AI to understand and generate code more accurately when dealing with large, complex codebases stored in different locations, facilitating more efficient AI-powered code generation and analysis.

Algorithmic Trading Intern

MathworksPart-time EmployeeAug 2023 - May 2024 • 10 mos● Collaborated on the development of an advanced trading simulation platform by working closely with MathWorks engineers to integrate a backtester—part of MathWorks’ Financial Toolbox—into a streamlined process that transitions seamlessly from backtesting to live algorithmic trading, ensuring error-free execution. enhancing trading strategy validation. ● Engineered a command reconfiguration feature that enabled real-time translation of backtesting rules into live trading commands, directly interfacing with Bloomberg’s Execution Management System (EMSX) for automated order routing and execution. ● Developed solutions to eliminate the need for rewriting simulation code for production trading, optimizing the workflow, improving the efficiency of the trading process and reducing the risk of discrepancies between backtested and live trading strategies. ● Spearheaded the implementation of an object-oriented programming approach, encapsulating data and functions to mirror the Bloomberg trading interface, while maintaining the flexibility to work without any modifications to the existing MATLAB backtester. ● Enhanced the MATLAB Financial Toolbox by integrating the trading simulation platform, providing MathWorks with a product that outperforms existing market solutions. ● Contributed to a billion-dollar product line by expanding the functionality of MathWorks' Financial Toolbox, making it more attractive to hedge funds and banks looking for an advanced algorithmic trading solution.

Trade Balance Sheet and Capital Management Summer Analyst

CitiInternJun 2023 - Aug 2023 • 3 mos● Conducted in-depth analysis of CECL & CCAR using SQL queries and Excel, reducing LGD miscalculations by 20% and improving the teams’ regulatory compliance. ● Analyzed and corrected 200+ LGD metrics for CECL/CCAR using Python scripts and data visualization tools, enhancing risk assessment accuracy. ● Developed a new Client Cost Factor Methodology using Monte Carlo simulations and optimization algorithms, leading to a 12% increase in pricing efficiency across new transactions involving both ICG and TTS Finance teams. ● Led project which reviewed client capital calculations related to Citi’s G-SIB Score component of TCE and created capital reallocation algorithm using Python to improve accuracy in Client Interface Warehouse. ● Integrated machine learning algorithms with existing credit risk models using Python and R to enhance prediction accuracy by 18% and aid in the development of more robust optimization strategies.

Education

Columbia University

Bachelor of Science, Operations Research and Financial EngineeringAug 2022 - May 2024

Bard College

Bachelor of Arts, Pure Mathematics and EconomicsJan 2020 - May 2022

How Pangea Works

Effortlessly discover top talent

We’ve distilled the candidate search from endless hours down to just a few minutes. Using Pangea’s AI-powered search tools, you can find top fractional talent able to take on your next project. Our system looks at your company’s niche and your needs to find the perfect match faster than any traditional hiring platform.

Start working with talent today

The top talent on Pangea is ready to get started with you right now. You can message or hire a candidate right from their profile page and start assigning work as soon as they respond. And the best part? Pangea’s fractional contract structure lets you start small and ramp up as your needs change, keeping your costs manageable and your team’s capabliities flexible.

Track work and invoices in one place

Assign tasks, track progress, and complete invoices all on Pangea. We’ve combined every part of the hiring process into one platform to eliminate the miscommunication that’s unavoidable on other freelance platforms. We even send out 1099s to your contractors at the end of the year!

Talk with a Talent Expert

Members of our team are available to help you speed through the hiring process.

Available Now

Book a Call