Aryeman G.

Key Skills

Software

No software listed

Top Subject Matter

Bioinformatics Domain Expertise

peptide–MHC stability prediction

cancer research (computational)

Top Data Types

Video

Top Task Types

Data Collection

Freelancer Overview

Research Intern — peptide–MHC stability prediction pipeline (NetMHCstabpan). Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Docker, Snakemake, and NetMHCstabpan. Education includes Bachelor of Science, University of Wisconsin–Madison (2027) and Research Internship, MD Anderson Cancer Center (2025). AI-training focus includes data types such as Medical, DICOM, and Computer Code and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

Co-Founder & Quantitative Strategist — sentiment score model and systematic strategy pipeline

You architected and deployed systematic options sentiment and risk-modeling components to generate quantitative trading signals and evaluate outcomes for client portfolios. You processed large-scale option-chain data to support model-driven strategy execution and performed operational scaling for multi-client deployment. You engineered risk constraints and dynamic hedging rules to govern model outputs and trading execution. • Architected an options sentiment score model powering $6.2M AUM across 15 HNW clients with $540K net profits (2025). • Deployed 12+ systematic options sentiment strategies using Interactive Brokers and Databento APIs; processed 2.5M+ daily option-chain datapoints for S&P 500. • Engineered a risk engine enforcing position limits and portfolio heat per trade plus dynamic Delta hedging. • Built an automated signal pipeline that scaled from 3 to 15 clients in 18 months with 94% retention.

2023 - Present

Research Intern — peptide–MHC stability prediction pipeline (NetMHCstabpan)

During the internship, you operationalized peptide–MHC stability modeling as a reproducible prediction workflow across multiple lab environments. You benchmarked runtime and output consistency between Dockerized and local execution to improve reliability of model inference. You integrated stability scoring into a Snakemake pipeline with validation and quality-control checks for malformed inputs. • Dockerized and deployed NetMHCstabpan predictions across 6 lab machines and 3 OS environments. • Reduced median end-to-end runtime by 35% and eliminated 4 environment-specific failures. • Added QC checks that flagged 9% of malformed inputs pre-run. • Validated results on 18 test samples within the Snakemake workflow.

2025 - 2025

Data Science Intern — WellnessVIP API and performance improvements

Data Collection

You built a data-driven API service for a wellness platform and improved downstream performance for physician queries. You enhanced database performance through schema indexing, improving data retrieval latency for large user/account sets. You also implemented a role-based access control layer to reduce detection time for production issues. • Built two API endpoints in Java Spring Boot and reduced physician query latency by 40%. • Optimized MySQL schema using four added indexes, cutting load time from 4.2s to 1.1s for 120+ physician accounts. • Implemented RBAC security to improve operational robustness. • Reduced production issue detection time by 37%.

2024 - 2024

Education

Work History