ML Engineer & Bioinformatician | Python | Cancer Genomics | Deep Learning | Delivering 97–98% Accuracy Models | BS Bioinformatics | Research-Driven & Results-Focused

I am Muhammad Nadeem, a BS Bioinformatics graduate from Government College University Faisalabad, Pakistan, with a strong foundation in machine learning, deep learning, cancer genomics, and computational biology.
I bridge the gap between biological science and artificial intelligence — building predictive models, analyzing genomic datasets, and delivering clean, reproducible, well-documented Python pipelines that generate real results.
What I bring to your project:
My ML projects speak for themselves. I built an attention-based deep learning model achieving 98.2% accuracy for breast cancer classification with interpretable heatmaps for clinical transparency. My breast cancer tumor classifier using Random Forest achieved 97.37% accuracy and 0.9962 AUC-ROC on the Wisconsin dataset. I also developed a molecular solubility prediction model achieving R²≈0.88 for drug discovery applications.
Beyond ML, I have hands-on bioinformatics experience from my internship at Genomac Institute Inc., where I worked on cancer genomics, mutation analysis, variant annotation, and genomic data interpretation. I am proficient in tools including NCBI-BLAST, MEGA, IGV, cBioPortal, ANNOVAR, VEP, TCGA, and COSMIC.
My machine learning internship at K2X Tech gave me real industry experience in data preprocessing, feature engineering, EDA, computer vision model development, and collaborative team workflows using GitHub and Jupyter.
Core Technical Skills:
Machine Learning: Logistic Regression, SVM, Random Forest, XGBoost, ANN, CNN, Visual Transformers

Python Libraries: pandas, NumPy, scikit-learn, TensorFlow, Keras, Biopython, Matplotlib, Seaborn

Bioinformatics: NGS Data Analysis, Variant Annotation, VCF Handling, Phylogenetic Analysis, GWAS, Immunoinformatics, Proteomics

Other Tools: R, Bash, Linux, Tableau, GitHub, Google Colab, Kaggle, VS Code
Why work with me:
I am analytical, detail-oriented, and deeply committed to quality. I deliver on time, communicate clearly, and always provide clean code with documentation. I treat every project as a research collaboration — your problem matters to me.
Whether you need a machine learning model, bioinformatics data analysis, genomic data interpretation, EDA and visualization, or research assistance — I am ready to help.
Let's build something impactful together.

Work Terms

Communication:

I respond within 2 hours, typically much faster. I provide regular updates throughout the project and am available via Guru messages during Pakistan Standard Time (GMT+5) business hours.

Project Start:

I kindly ask all clients to message me before placing an order so we can clearly define requirements, timeline, and deliverables. This ensures the best possible outcome for both parties.

Revisions:

I offer reasonable revisions to ensure complete satisfaction. My goal is that you are 100% happy with the final deliverable.

Deliverables:

All projects include clean, commented, well-structured code. ML projects include a summary report of model performance, evaluation metrics, and visualizations. Bioinformatics projects include annotated results and interpretation notes.

Timeline:

Small tasks (EDA, visualization, data cleaning): 1–2 days

Medium projects (ML model development): 3–5 days

Large projects (end-to-end pipeline, research analysis): 7–14 days

Payment:

I work with Guru SafePay for full security and transparency. Milestone-based payment is preferred for larger projects.

Confidentiality:

All client data and project details are kept strictly confidential. I do not share, publish, or reuse any client data without explicit written permission.
I look forward to building a long-term professional relationship with you.