Hire the Best Bioinformatics Developers
in the United States

I'm a retired academic with 30 years' experience in life-science research, education and publishing. So I understand your problem, as I've spent decades helping people just like YOU. Here’s how I can help with your scientific or medical project: –Literature searches, systematic reviews and meta-analyses –Experimental design and sample size estimation –Descriptive statistics and data visualization –Advanced multivariate modeling and hypothesis testing –Technical illustrations, graphical abstracts and flowcharts –Content editing for theses, articles, grants, fellowship applications and full-length books –Copy editing for grammar, logic, brevity, flow and adherence to academic citation styles –Fact-checking sources to root out false claims and hallucinated references –General coaching, strategizing and career development for life-science researchers at any career stage, whether you are a prospective graduate student, PhD candidate, postdoc or tenured faculty member. Everyone needs a helping hand from time to time. I can start from scratch or work with YOUR existing materials. I’m skilled with tools like PubMed, EndNote, Zotero, LaTeX, Prism, R Studio, Photoshop and Illustrator. For more advanced bioinformatics tasks, I use Expasy, GEO, NCBI, UniProt, and genome browsers like Ensembl and UCSC. As my postdoc advisor once said, "You can explain it to 100 people one at a time, or you can write a great set of instructions." So if you need a manual, protocol, or Standard Operating Procedure (SOP), I can help with that too. Using my deep experience writing clear instructions for labs and classrooms, I can cover every topic: experimental workflow, equipment maintenance, how-to guides or whatever might be your critical need. A little more about ME: I have a BA from Yale and a PhD from the University of Chicago. I led an NIH-funded research lab for 23 years and published 25+ peer-reviewed journal articles. I’ve reviewed over 50 scientific manuscripts and scored grants for the NIH, NSF, and DOD. As a full Professor I taught cell biology, histology, human development, ecology/evolution, epidemiology and statistics at university. In 2024 I semi-retired by starting my own scientific consulting company, offering fractional services to principal investigators, healthcare providers, biotech startups, scientific societies, health- and environment-focused non-profits, and independent entrepreneurs. And let's end with US. Because together, we might be unstoppable.

A dynamic Senior Biostatistician and Data Scientist seeks to bring an accomplished combination of education and experience to an industry-leading employer. 15+ years of experience in related data analysis, computer programming, and instruction roles for distinguished universities. Ph.D. in Biostatistics, with an M.S. in both Bio-Engineering and Applied Mathematics. Proficient in data management, mathematical modeling, grad/undergrad instruction, longitudinal/statistical analysis, project management, and more. Diligent and goal-oriented, with the skills, education, and hands-on experience needed to make an immediate impact as part of any fast-paced team.

I am an AI/ML Engineer with 8 years of experience and PhD-trained Bioinformatics Scientist. I specializes in developing production-quality AI systems, ETL/Data Pipeline modeling, deep learning, NLP/LLM workflows, and digitally using AI for pathology. As an experienced hands-on builder of end-to-end AI systems for pharmaceutical research and development (R&D), cancer research, and computational pathology, I have developed AI systems that integrate raw data into production ML application systems from the data pipeline through to deployment, monitoring, and statistical analysis for non-technical stakeholders. I have expertise in both cutting-edge research in the area of machine learning, as well as extensive practical engineering experience with scalable and high reliability ML application systems in production. 📌 Recent Project Experience ✨ Developed ML pipeline to process heterogeneous structured and unstructured data • Pfizer DSDR – Drug Safety AI Pipeline: Built production ML/ETL workflows integrating structured + unstructured data, with API deployment, validation, monitoring, and alerts. ✨ Trained and deployed deep learning networks that can analyze large biomedical data sets • FNLCR – Multi-Modal Pathology Toolkit: Operationalized HALO H&E/mIF whole-slide analysis and million-cell/pixel-scale metadata curation. ✨ Deployed and monitored AI algorithms in production environments with API, monitoring, validation, and cross-functional collaboration • AbbVie Precision Medicine – WSI Modality Prediction: Trained MIL deep learning models with attention heatmaps and Flask API visualization. 💡 What I Can Help You With ✅ Production ML Systems • End-to-end ML pipeline design and implementation • Model training, evaluation, deployment, and monitoring • API-based ML inference systems • Model reliability, robustness testing, and performance tracking ✅ ETL & Data Engineering for AI • Automated ETL pipelines for structured and unstructured datasets • Data validation, error handling, metadata management, and QA workflows • Integration of SQL databases, CSV files, imaging data, and distributed repositories • Scalable data curation pipelines for ML-ready datasets ✅ Deep Learning & Computer Vision • PyTorch/Keras model development • Vision transformers, foundation models, CNNs, MIL models, segmentation models • Image classification, prediction, feature extraction, and attention visualization • Large-scale image analysis for gigapixel whole-slide images ✅ Digital Pathology & Biomedical AI • Whole-slide image analysis for H&E, IHC, and multiplex immunofluorescence • Weakly supervised multi-instance learning for histopathology • Spatial omics, single-cell analysis, graph-based modeling, and image-derived biomarkers • HALO-based image analysis workflows and algorithmic scoring exports ✅ NLP/LLM & AI Workflow Integration • LLM-powered data processing and knowledge extraction workflows • Biomedical text/data integration • AI-assisted research pipelines and automation • Foundation model evaluation and applied AI system development ⚙ Technical Expertise Languages: Python(Advanced), SQL(PostgreSQL, MS SQL Server), R, Go AI/ML/DL: PyTorch, Keras, Statistical ML, Computer vision, MIL, Transformers, DNN, CNN NLP/LLM: RAG, LangChain, LangGraph LlamaIndex, OpenAI API, Anthropic Claude, Hugging Face, AutoGPT, AgentGPT Data/ETL: CSV, Structured/unstructured data integration, Metadata pipelines, Pandas, Numpy, Data validation Frontend: React, Next.js, TypeScript, HTML5, CSS3, Tailwind CSS, Material-UI Backend: Node.js, Express.js, GraphQL Databases: MongoDB, MySQL, Redis, Firebase Deployment: Flask, REST APIs, Linux/Unix, Git, Production ML workflows E-Commerce: Shopify (Liquid, Apps, Plus), WordPress, WooCommerce, Elementor DevOps: AWS, Docker, CI/CD, Nginx, PM2 Automation: n8n, Make, Zapier, Temporal, Apache Airflow CRM/Marketing: HubSpot, GoHighLevel, Salesforce, ActiveCampaign Data Visualization: Power BI, Looker Studio, Matplotlib, Plotly Domains: Digital pathology, Big Data, Statistical testing, Spatial Omics, Biomedical AI, Pharmaceutical R&D, Cancer research 🤝 Why Work With Me? ✓ PhD-level AI/ML expertise with real-world production experience ✓ Strong ability to bridge research, engineering, and domain science ✓ Experienced in working with pharmaceutical, biomedical, and cross-functional teams ✓ Clean, scalable, well-documented code and reproducible workflows ✓ Strong communication and attention to detail for complex technical projects I am particularly suited to taking on clients who require more than a typical ML developer, specifically those involved with highly complex biomedical data, multi-dimensional imaging, production ML systems and AI workflows that are built from research through to deployment. If you need assistance with creating an effective AI pipeline, deploying an ML model, developing a CV system, or analyzing digital pathology data, I would be glad to work with you on your project.

I’m a life sciences researcher and data analyst with an MS in Biotechnology (GPA 4.0, Florida Institute of Technology, 2026) and a BS in Biology with a minor in Animal Behavior (Indiana University, Magna Cum Laude). I build statistical workflows, analyze complex biological datasets, and write clearly for scientific audiences. During my graduate research at Florida Tech, I replaced a $1,000+/year paid data collection platform with a custom open-source R solution, designed automated field data workflows, and integrated multi-source environmental data into reproducible pipelines. As an undergraduate researcher at Indiana University, I analyzed multi-year GPS wildlife tracking datasets, cleaned long-term behavioral observation records, and built the lab’s first searchable specimen database from 40+ years of archival records. WHAT I CAN DO FOR YOU - Statistical analysis: regression, mixed-effects models, hypothesis testing, descriptive statistics - R and Python scripting and pipeline development - Data cleaning and transformation from messy, multi-source datasets - Publication-quality visualizations with ggplot2 and matplotlib - Reproducible reporting via R Markdown and Jupyter Notebooks - Scientific writing: Methods, Results, and Discussion sections - Literature reviews, grant background sections, and lay summaries - Manuscript editing for clarity, accuracy, and journal style My background spans field ecology, molecular biology, and computational data science. I work equally well with observational biological data, commercial analytics datasets, and structured clinical data. I’m detail-oriented, deadline-driven, and used to communicating complex findings to non-specialist audiences (I’ve taught college biology). Whether you need a quick data clean-up or a full analysis pipeline with a written report, I can help. Message me with what you’re working on. I reply within 24 hours.

Biostatistician of 3 years with 13 years of collective data analysis experience and proven track record of delivering data-centered narratives (15 published articles) in diverse disciplines from -omics to healthcare research. My go-to tool is R/R-studio, I favor Bayesian methods, and I take pride in delivering expert-level services. Expert-level services: * Data management, analysis, and visualization * Review and editing academic writing (protocols, posters, abstracts, manuscripts, dissertation) * Study design consultation (power analyses, Bayesian operating characteristics) * 1:1 mentorship and training on R coding, research methods, project management, data management Skills: R/R-studio, Data analysis, Project management, Database development (REDCap expert), Dashboards (PowerBI) , Data wrangling, Bayesian methods, Monte Carlo Simulations, Causal Inference (propensity scores, standardization, difference-in-difference-DiD, synthetic controls) Credentials: * Practicing biostatistician that leads clinical trials, observation, and quality improvement studies in the area of oncology at a cancer institute * PhD in quantitative biology * 16 peer-reviewed publications in the areas of surgical oncology, medical oncology, quantitative genetics, evolutionary physiology, genomics, gene expression, and study design.

I science. It's a verb! After 20 years doing academic research, I now provide big data computational biology services for biotech R&D, because I enjoy working on useful projects that yield tangible results. Having advised Fortune-100 companies (AbbVie, Syngenta) and leading medical institutions (Mayo Clinic), I bring a wealth of experience in bioinformatics, genomics and multi-omics, particularly for high-volume, high-throughput data analysis. I excel in data analyses, data management, mathematical modeling, computer simulations, analytics and production workflow deployment on local computers, clusters and the cloud.