Daniel Wanjala.

My Data Science Toolkit & More

I approach data science as a discipline for decision-making, not just model-building. My work emphasizes robust data pipelines, reproducible experimentation, and stakeholder-focused outcomes: models are valuable only when they inform better choices. I balance classical statistical rigor with modern deep-learning approaches, favoring solutions that are interpretable, resource-efficient, and deployable in real-world, resource-constrained environments.

From building neural-network driven investment platforms to optimizing hospital operations, my skills span the full data science lifecycle. Dive in and explore the capabilities I bring to the table!

The Technical Arsenal

Expert

Code & Data Wrangling

Fluent in Python, SQL, and data cleaning. I turn chaos into structured, actionable data.

  • Python (Pandas, NumPy, Scikit-learn) Pro Used in all my data projects
  • SQL & Database Management Advanced Optimized queries for large datasets
  • Git & Version Control Pro Collaboration & code history
Proficient

Machine Learning & AI

Supervised learning, neural networks (MLPs, RNNs, CNNs, LSTMs), ensemble methods, anomaly detection, and time-series analysis.

  • Supervised Learning & Ensemble Methods Pro Classification, regression, Random Forest, XGBoost
  • Neural Networks (MLPs, RNNs, CNNs, LSTMs) Advanced TensorFlow, Keras for deep learning & research
  • Anomaly Detection & Time-Series Analysis Pro Class imbalance handling, cost-sensitive learning
Proficient

Data Visualization

Transforming complex data into clear, actionable insights through compelling visualizations.

  • Matplotlib & Seaborn Pro Beautiful static plots
  • Plotly & Dash Advanced Interactive dashboards
  • Power BI & Tableau Learning Business reporting

Skill Snapshot: Where I Shine

Quantifying skills is tricky (it's not like they have hit points!), but here's a rough gauge of my comfort level and experience with key areas. Consider these 'confidence bars' – always growing!

Python for Data Science Highly Proficient
Predictive Modeling Proficient
SQL & Databases Proficient
Data Visualization (Python Libs) Proficient
Deep Learning (TensorFlow/Keras) Intermediate
Cloud Platforms (GCP/AWS) Foundational

Favorite Tools of the Trade

Python Python ML
SQL SQL/MySQL DB
PostgreSQL PostgreSQL DB
Pandas Pandas Data
NumPy NumPy ML
Scikit-learn Scikit-learn ML
TensorFlow TensorFlow ML
PyTorch PyTorch ML
Jupyter Jupyter Notebooks Notebook
Matplotlib Matplotlib Viz
Seaborn Seaborn Viz
Plotly Plotly Viz
Power BI Power BI Viz
Tableau Tableau Viz
Git Git DevOps
Docker Docker DevOps
Kubernetes Kubernetes DevOps
AWS AWS Cloud
GCP Google Cloud Cloud
VSCode VSCode IDE
Streamlit Streamlit App
FastAPI FastAPI API
MongoDB MongoDB DB
Redis Redis DB
Flask Flask API
Django Django API
React React Frontend
OpenCV OpenCV CV
Apache Spark Apache Spark Big Data
Hadoop Hadoop Big Data

Beyond the Tech: The Human Element

Problem Solver

Problem-Solving

Deconstructing complex issues, identifying root causes, and devising effective, data-driven solutions.

Leader

Leadership & Teamwork

Experience leading IT interns and collaborating effectively within teams to achieve shared goals.

Researcher

Research & Documentation

Methodically investigating problems, exploring solutions, and clearly documenting findings and processes.

Adaptive

Adaptability & Learning

Thriving in dynamic environments, quickly learning new technologies, and embracing continuous improvement.

Always Learning, Always Growing

The world of data science is a marathon, not a sprint (though sometimes deadlines feel like sprints!). I'm committed to lifelong learning, staying curious, and formally expanding my knowledge base through certifications and ongoing education like my current MSc program. Here are a few badges I've picked up along the way:

Google Cloud Admin Intro HackerRank Software Engineer HackerRank Problem Solving (Int.) Google Data Foundations HackerRank Python (Basic) Udemy: Python for Data Science

The Evolution of My Data Journey

Every skill has a story. Here's how my data science toolkit evolved over time, from basic programming to advanced machine learning. Hover over each milestone to see the impact!

The Foundation

Python basics, SQL fundamentals, and the first taste of data analysis

Key Milestones

  • • First Python script
  • • Basic SQL queries
  • • Introduction to Pandas

Achievements

  • • First ML model deployment
  • • Data visualization mastery
  • • Advanced SQL optimization

The Growth Phase

Advanced analytics, machine learning, and real-world applications

Deep Learning Era

Neural networks, computer vision, and advanced ML techniques

Breakthroughs

  • • TensorFlow/Keras expertise
  • • Computer vision projects
  • • Cloud platform integration

Current Focus

  • • Advanced NLP techniques
  • • MLOps & deployment
  • • Research & innovation

The Future Unfolds

Pushing boundaries with cutting-edge AI and data science

Ready to Apply These Skills?

My skills are more than just lines on a resume; they're tools ready to be deployed on challenging projects. If you see a potential fit or just want to chat about data, let's connect!

Let's Talk Data