Adam Lawal

Data Scientist & Software Engineer

| LinkedIn | GitHub

About

Highly motivated and results-oriented professional with a strong foundation in Data Science, Statistics, and Software Engineering. Proven ability to leverage AI/ML, data analysis, and full-stack development skills to drive impactful solutions, reduce inefficiencies, and enhance user engagement. Adept at leading projects, collaborating in team environments, and translating complex data into actionable insights. Eager to apply analytical prowess and technical expertise to challenging roles in data science and AI.

Work Experience

Software Engineering Intern (High School Internship Program)

Microsoft ADC

Dec 2025 - Present

Internship focused on developing a proximity-based waste management system to optimize collection processes.

  • Led a 5-person team in collaboration with a mentor to develop a proximity-based waste management system, reducing waste collection inefficiencies by 25%.
  • Programmed Arduino sensors and implemented C++ logic for real-time bin monitoring and optimized scheduling.
  • Developed functional prototypes using Tinkercad, CNC machines, and 3D printing technologies.

Data Science Intern (Intensive Training Program)

Yomi Denzel Foundation

Dec 2025 - Present

Intensive training program focused on developing an AI-powered fitness platform.

  • Spearheaded the development of HealthRec, an AI-powered fitness platform that translated health metrics into conversational insights, resulting in a 10% reduction in user churn and increased engagement.
  • Engineered the backend using Django, integrating the Google Fit API and processing user health data with Pandas and NumPy for personalized analytics.
  • Implemented OpenAI API integration to provide real-time, data-driven recommendations via a modular and dynamic React user interface.

Education

Statistics

University of Lagos

Courses

  • Statistical theory, probability distributions, inference, and regression modeling (linear, logistic, time series analysis)
  • Multivariate methods, Bayesian statistics, experimental design, and applications across public policy, economics, and health sciences
  • Statistical computing and data analysis using Python, R, SQL, and modern simulation techniques

Data Science

AltSchool Africa

Courses

  • Acquiring foundational skills in data cleaning, analysis, and visualization using Python libraries (NumPy, Pandas, SciPy, Matplotlib, Seaborn)
  • Exploring introductory machine learning techniques, including regression models, decision trees, and neural networks

General Studies

Homat Comprehensive College

4.5/5.0 GPA

Courses

  • Calculus
  • Data Processing
  • Science

Projects

ALX Nigeria Exploratory Data Analysis

Personal project focused on uncovering performance and engagement trends within a large learner dataset.

Cryptocurrency Market Analysis

Personal project involving in-depth analysis and visualization of cryptocurrency market trends.

Medset (Cofounder & Public Relations Officer)

Co-founded Medset, an initiative under SAGE (Students for the Advancement of Global Entrepreneurship) focused on improving healthcare access through technology.

Awards

School Management Scholarship

Homat Comprehensive College

Awarded for academic excellence at Homat Comprehensive College.

FATE Scholarship

Homat Comprehensive College

Recognized for outstanding potential and achievement through the FATE Scholarship.

1st Place - SAGE World Cup

SAGE (Students for the Advancement of Global Entrepreneurship)

Secured first place at the SAGE World Cup while representing Nigeria, competing against participants from over 15 countries.

Skills

Programming Languages

  • Python
  • C++
  • R
  • SQL

Tools & Technologies

  • scikit-learn
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Tinkercad
  • Langchain
  • Django
  • React
  • Git
  • Arduino
  • CNC Machines
  • 3D Printing
  • Google Fit API
  • OpenAI API

Data Science Concepts

  • Supervised Learning (Regression, Classification)
  • Unsupervised Learning (Clustering, Dimensionality Reduction)
  • Data Wrangling
  • Object-Oriented Programming (OOP)
  • Retrieval-Augmented Generation (RAG)
  • Statistics
  • Bayesian Statistics
  • Experimental Design
  • Time Series Analysis
  • Regression Models
  • Decision Trees
  • Neural Networks