Data Scientist . Machine Learning Engineer . Analytics Builder

Muhammad Abdulsalam

I work with messy data, machine-learning models, dashboards, experiments, and business questions. Applied AI and RAG are part of the toolkit, but the center is data science: turning evidence into decisions.

Portrait of Muhammad Abdulsalam
data, models, and the notes behind the work
63 documented projects
29 machine-learning builds
11 EDA and dashboard projects
13 AI and LLM systems
01

Data Analysis + Storytelling

Exploratory notebooks, cleaning workflows, feature investigation, visual explanation, dashboards, and stakeholder-readable insights.

02

Machine Learning

Classification, regression, clustering, forecasting, NLP, recommender systems, computer vision, and deep-learning experiments.

03

Statistics + Experimentation

A/B testing, Bayesian comparison, causal-thinking examples, partial correlation, metric design, and honest model evaluation.

04

Applied AI + Data Tools

RAG assistants, document QA, Flask APIs, Streamlit apps, Dockerized models, scrapers, and practical tools around data workflows.

professional signal

Experience

Client-facing data science, part-time AI engineering, and classroom teaching around AI and data structures.

2022 - Present

Freelance Data Scientist & AI Engineer

Delivered client work across churn prediction, forecasting, clustering, incident modeling, dashboards, reports, APIs, and reusable Python workflows.

Apr 2023 - Apr 2025

AI Engineer, Say Hai

Built customer AI workflows and lightweight web tools with Python, OpenAI/Claude APIs, Flask, GCP, LangChain, LangFlow, n8n, Gradio, and Streamlit.

Sep 2024 - Feb 2025

AI Teaching Assistant

Taught Artificial Intelligence and Data Structures, supported hands-on coding exercises, mentoring, grading, and technical explanation.

current data orbit

What I am sharpening now

Strengthening data-science judgment: better analysis habits, clearer evaluation, stronger storytelling, and models that connect to business decisions instead of stopping at notebook scores.

Current focus

Creative Archive

Data science is the front door. The writing, art, music, and books are the deeper context: the taste, curiosity, and emotional attention behind the systems.

contact + resume

For work conversations

If the projects feel aligned with what you are building, the resume is here as a compact professional summary.