Ignacio Ibarra
Verified Expert in Engineering
Bioinformatics Developer
Frankfurt, Hesse, Germany
Toptal member since September 19, 2025
Ignacio is a PhD-trained computational biologist and ML researcher with 10+ years of experience in academia and industry. He has designed data workflows, built generative models, and led genomics/bioinformatics research. Passionate about applying data engineering and modeling to complex systems spanning biology to business, Ignacio is skilled in data engineering, ML, automation, LLMs, CI/CD, deployment, Agile cycles, and clear milestones.
Portfolio
Experience
- Research - 14 years
- Bioinformatics - 14 years
- Python 3 - 14 years
- Biochemistry - 14 years
- Genomics - 12 years
- Machine Learning - 8 years
- Algorithmic Trading - 4 years
- Cursor AI - 2 years
Preferred Environment
Windows, Cursor AI, Slack, Python 3, GitHub, Machine Learning, Python, Data Science, NumPy, Big Data, SQL, Scikit-learn, Excel 365, PDF, Statistical Analysis, Data Analytics, Cloud Platforms
The most amazing...
...graph-based deep learning framework I've developed predicts genomics counts using sequence features and cell-cell relationships.
Work Experience
Independent ML Consultant
Online Freelance Agencies
- Acted as a senior AI training specialist, implementing STEM reasoning for LLMs.
- Delivered production-ready algorithmic workflows with 100% approval.
- Advised clients on ML-deployment strategies, reducing cost in cycle-based projects.
Director
Bioptimus
- Led model development of a "ChatGPT for Biology" within an early biotech team.
- Defined a technical roadmap and shipped the MVP within two quarters, enabling industry collaborations.
- Analyzed, using statistical modeling, the MOSAIC data bank (Owkin licensed), identifying and validating target features significantly associated with clinical phenotypes in five cancer indications.
Scientist
Helmholtz Zentrum München
- Developed generative models for transcriptomic perturbations.
- Benchmarked workflows for single-cell atlases, improving computing times by 50%.
- Designed and applied biophysical machine learning to study cell transitions.
- Contributed to more than five peer-reviewed publications cited more than 3,000 times.
- Coordinated large-scale consortium projects across 5+ international labs.
Scientist
EMBL
- Developed QC-approved workflows for omics data, including scATAC, RNA, and ChIP/SELEX-seq.
- Led international collaborations and reproducible project execution.
- Published 5+ papers in high-impact journals. Code and methods were reused in follow-up projects across international collaborations and patents.
- Acted as a reviewer and speaker at leading conferences.
Research Assistant
Bioinformatics Laboratories
- Developed novel DP-algorithms in Devos Lab for protein structure alignment. Reduced computation time in structural comparisons by over 25%.
- Built models for structural bioinformatics for Melo Lab. Wrote a toolkit to learn introductory bioinformatics algorithms, used in intro courses.
- Modeled DNA/protein-DNA structures via spatial restraints for Madhusudhan Lab. Provided early structural models for docking studies, accelerating experimental design.
Experience
MuBind | Learning Sequence-based Regulatory Dynamics in Single Cells
http://github.com/theislab/mubindDarvasAI | TradingView Indicator and Website for Weekly Breakouts.
Education
PhD in Computational Biology
Ruprecht Karl University of Heidelberg - Heidelberg, Germany
Master's Degree in Biochemistry and Computer Science
Pontifical Catholic University of Chile - Santiago, Chile
Skills
Libraries/APIs
PyTorch, NumPy, Pandas, TensorFlow, Scikit-learn, OpenAI API, Beautiful Soup, Python Asyncio, PySpark, Coinbase API
Tools
GitLab, GitHub, Snakemake, Seaborn, AI Prompts, Slack, GitLab CI/CD, AWS Command Line Interface (CLI), Amazon SageMaker, Notion, AWS Copilot
Languages
Python 3, Python, SQL, R, Pine Script, Snowflake, C#
Paradigms
ETL, Mathematical Optimization, Agile
Platforms
Windows, Amazon Web Services (AWS), Docker, Ubuntu, Amazon EC2, Visual Studio Code (VS Code), Google Cloud Platform (GCP)
Industry Expertise
Bioinformatics
Storage
JSON, Data Validation, Graph Databases, Amazon S3 (AWS S3), MongoDB, PostgreSQL
Frameworks
Selenium, .NET, Spark
Other
Cursor AI, Biochemistry, Research, Computational Biology, Mathematics, Genetics, Computational Genomics, Structural Biology, Machine Learning, Programming, Exploratory Data Analysis, Wofkflow, Cancer Genomics, Trading, TradingView, Optimization, Prompt Engineering, Data Analysis, Dash, Algorithmic Trading, Data Science, Big Data, Large Language Models (LLMs), ChatGPT Prompts, Vector Databases, Evaluation, Predictive Modeling, Algorithms, AI Integration, AI Model Integration, Vectorization, Training, Training Workshops, Feature Engineering, Modeling, Data Visualization, Excel 365, Reports, FASTA, Charts, DNA Sequencing, Biometrics, RNA Sequencing, Graphs, Statistical Analysis, Markov Model, Data Analytics, Automation Tools, Image Processing, Software Engineering, Biotechnology, Statistics, Transformers, Web Scraping, Financial Data, Artificial Intelligence (AI), Reinforcement Learning, Natural Language Processing (NLP), Reinforcement Learning from Human Feedback (RLHF), Generative Artificial Intelligence (GenAI), APIs, Knowledge Graphs, graph embeddings, Centrality Measures, Community Detection, pathfinding, Algorithmic Graph Theory, Conversational AI, Workflow, Demand Forecasting, Demand Planning, Sales Forecasting, Forecasting, PDF, Microbiology, Shapley, Cloud Platforms, Optical Character Recognition (OCR), Neural Networks, Causal Inference, Biology, Computer Science, Genomics, Data Engineering, Biomedical Informatics, Amazon Neptune, Trading Bots, Slurm Workload Manager, Structural Bioinformatics, Deep Learning, Software Development, Pricing Models, Pricing, Machine Learning Operations (MLOps), Agentic AI, Retrieval-augmented Generation (RAG), Chatbots, Equity, Equity Market Data, Financial Markets, Meta Llama, Hugging Face, Sentiment Analysis, Airtable, API Integration
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