{ "meta": { "version": "v1.0.0", "canonical": "https://github.com/jsonresume/resume-schema/blob/v1.0.0/schema.json" }, "basics": { "name": "Arash Behmand", "label": "Machine Learning Scientist", "email": "arash.behmand@gmail.com", "phone": "(+44) 759 3359 776", "location": { "countryCode": "UK", "city": "London", "address": "London, UK" }, "profiles": [ { "network": "GitHub", "username": "arashbehmand", "url": "https://github.com/arashbehmand" }, { "network": "LinkedIn", "username": "arashbehmand", "url": "https://www.linkedin.com/in/arashbehmand/" } ], "summary": "Machine Learning Engineer with a decade of experience developing and deploying ML models and applications using Python, LangChain, PySpark, and AWS. Expertise in applying Large Language Models (LLMs) and Generative AI to create innovative solutions. Proven ability to build scalable data infrastructures and automate data pipelines with Airflow. Seeking a challenging role contributing to cutting-edge AI advancements." }, "work": [ { "position": "AI / ML Scientist", "company": "Builder.ai", "name": "Builder.ai", "startDate": "2025-01-01", "endDate": "2025-05-01", "location": "London, UK", "summary": "Pioneered AI-driven automation of feature documentation at scale for 500+ projects, designing end-to-end Python/LLM systems that reduced manual documentation from 10+ hours to 1 hour per project. Enabled ingestion of complex design whiteboards and multi-source data, significantly enhancing requirement coverage, product understanding, and team efficiency.", "highlights": [ "Developed a modular Python and LangChain-based platform that automated generation of detailed feature notes across 500+ projects, cutting documentation time from 10+ hours to 1 hour and achieving 88% F1 accuracy and 85% requirement coverage.", "Engineered a multi-stage LLM pipeline to extract and synthesize requirements from 4–5 call transcripts and design documents per project, leveraging an Aggregate of Experts (AoE) approach to maximize recall and contextual depth.", "Built an AI-powered system to interpret large SVG whiteboard diagrams (10–15 images, 70+ components each), converting them into comprehensive Markdown docs and relationship graphs, enabling richer blueprinting and seamless integration with downstream AI workflows." ] }, { "company": "AI Andromeda", "position": "Co-Founder & Machine Learning Engineer", "name": "AI Andromeda Ltd.", "startDate": "2024-04-01", "endDate": "2024-12-01", "location": "London, UK", "summary": "Developing an AI-powered platform to automate and streamline the job application process using LLMs and LangChain.", "highlights": [ "Created a Job Seeker AI Platform that automates job matching, company research, resume tailoring, and cover letter generation using LLMs and LangChain.", "Integrated APIs to fetch job postings and user data from platforms like LinkedIn, enabling automated job matching and personalized recommendations.", "Designed a system to crawl and consolidate company insights from sources like Crunchbase, Glassdoor, LinkedIn, and news outlets, providing users with comprehensive research on potential employers.", "Built features to tailor resumes and generate cover letters dynamically, improving job application throughput by 5×.", "Created tools to manage communications, including LinkedIn messages and emails, enhancing efficiency in job search workflows.", "Engineered a scalable infrastructure on AWS to handle high-throughput demands while maintaining consistent performance." ] }, { "company": "SnappyShopper LTD", "position": "Senior Data Scientist", "name": "SnappyShopper LTD", "startDate": "2022-01-01", "endDate": "2024-03-01", "location": "Dundee, Scotland", "summary": "Solely architected and established data infrastructure from scratch, demonstrating leadership and expertise in data engineering by building a PostgreSQL data warehouse, creating Airflow pipelines for automated data processes.", "highlights": [ "Delivered a graph-based anomaly detection system, identifying 7% of users exploiting promotional offers, reducing fraudulent activity by 20%.", "Designed a scoring-based ranking system for candidate stores using factors like IMD score and demographics, increasing store activation success rate from 20% to 60%.", "Applied causal inference methods through A/B testing and campaign analyses to optimize pricing strategies and marketing initiatives, resulting in a 15% increase in revenue and improved customer engagement.", "Created interactive dashboards in Tableau and Metabase for centralized KPI tracking, providing actionable insights to managers and executives." ] }, { "position": "Senior Machine Learning Engineer", "company": "Divar", "name": "Divar", "startDate": "2017-07-01", "endDate": "2021-09-01", "location": "Iran", "summary": "Led efforts to scale the platform's user base from 2 million to over 30 million by developing data-driven solutions across data science, engineering, and analytics, enhancing platform performance and user engagement.", "highlights": [ "Built and deployed an XGBoost-based machine learning model for fraud detection, reducing reported scams by 32% and investigation time by 80%.", "Established a new recruitment business line worth $3 million by conducting market analysis using clustering and NLP techniques.", "Devised detection mechanisms for bot activity, leading to a 40% reduction in phishing scams by uncovering that 5–10% of users accessing contact data were bots.", "Engineered a crawler bot detection model using feature engineering and advanced data analysis techniques, reducing fraudulent listings by 25% and improving user trust.", "Incorporated active learning and NLP techniques (LM embeddings, word clustering, named entity recognition) to improve search algorithms, reducing bounce rate from 20% to 15% and decreasing dark queries by 50%.", "Created 10+ crawler bots for competitor analysis, providing strategic insights into market positioning and informed decision-making.", "Optimized ETL pipelines to process 2 TB/day of data, implementing fault monitoring and error handling, reducing failure rates by 40× and increasing data reliability." ] } ], "education": [ { "studyType": "MSc", "area": "Artificial Intelligence", "institution": "Sharif University of Technology", "startDate": "2012-09-01", "endDate": "2015-12-01" }, { "studyType": "BSc", "area": "Electrical Engineering - Control Engineering", "institution": "Amirkabir University of Technology", "startDate": "2009-09-01", "endDate": "2012-07-01" } ], "skills": [ { "name": "Programming Languages & Libraries, Data Analysis & Visualization", "keywords": [ "Python", "C++", "SQL", "JavaScript", "Pandas", "Scikit-learn", "Keras", "PySpark", "LangChain", "XGBoost", "Data Analysis", "Tableau", "Metabase" ] }, { "name": "Machine Learning & AI, Data Engineering", "keywords": [ "NLP", "Deep Learning", "Computer Vision", "Prompt Engineering", "LLMs", "ETL Pipeline Development", "Airflow", "PostgreSQL", "AWS", "Kafka" ] } ], "projects": [ { "name": "TLDR Telegram Bot", "startDate": "2023-01-01", "endDate": "2024-03-01", "summary": "Developed a Telegram bot using LangChain and generative AI to summarize and maintain context in group chats, enhancing communication within personal networks.", "url": "https://github.com/arashbehmand/telegram-tldr-bot" }, { "name": "Search1API Plugin Library for LangChain", "startDate": "2023-01-01", "endDate": "2024-03-01", "summary": "Enhanced the LangChain framework by developing a plugin library for Search1API, expanding the framework's capabilities.", "url": "https://github.com/arashbehmand/langchain_search1api" }, { "name": "GenAI-based Study Note Creator", "startDate": "2023-01-01", "endDate": "2024-03-01", "summary": "Crafted a study note generator utilizing LangChain and generative AI to produce companion study notes for books, articles, and video courses.", "url": "https://github.com/arashbehmand/note-extractor" }, { "name": "UK Rent Automation", "startDate": "2022-01-01", "endDate": "2024-03-01", "summary": "Automated property discovery by scraping data from Zoopla, Rightmove, and OpenRent, sending best matches to Telegram, reducing search time by 50% on average.", "url": "https://github.com/arashbehmand/uk-rent" }, { "name": "Better Amazon Ratings Extension", "startDate": "2022-01-01", "endDate": "2024-03-01", "summary": "Designed a web browser extension to display adjusted Amazon product ratings using Wilson score and review distributions, providing more accurate product assessments.", "url": "https://github.com/arashbehmand/amazon-beta-stars" }, { "name": "Isochronous Map Representation", "startDate": "2022-01-01", "endDate": "2022-12-01", "summary": "Produced a map representation displaying isochronous areas of a city based on travel time from a specific point." }, { "name": "FarsNet (Persian WordNet) Python Library", "startDate": "2012-01-01", "endDate": "2015-01-01", "summary": "Developed a Python library for Persian WordNet by reverse engineering the C# library provided by Shahid Beheshti University, enabling NLP research in Persian.", "url": "https://github.com/arashbehmand/farsnet" }, { "name": "Advanced DRM Deciphering of Persian Bookstore Apps", "startDate": "2017-01-01", "endDate": "2020-01-01", "summary": "Deciphered and reverse-engineered proprietary DRM mechanisms in three Persian bookstore apps, showcasing advanced technical expertise in overcoming complex challenges." } ] }