Back-end Engineer
(Java/Golang/Python/SQL)
Data/MLOps Engineer
(AWS/Kubernetes/Hadoop/Spark)
Patrick Ojunde
Lagos, Nigeria
B.A English Language,
Obafemi Awolowo University, Ile-Ife, Osun, Nigeria
patrickojunde@gmail.com | 234 810 470 8102
Patrick Ojunde is an experienced Java/Python software engineer. His passion for building intelligent systems led him to pursue a career as a machine learning engineer. He has worked on both personal and team-based data science projects; some of which include building predictive/time-series models deployed on the web via Flask & FastApi, and analytics dashboard built with Python, Tableau and Google Studio.
He is a regular article contributor of articles covering programming and machine learning on platforms like medium.com, thepythonhut.com etc.
He is currently open to entry level job as a software and/or machine learning engineer ready to work with teams and apply his knowledge of statistics, and skills in software engineering and machine learning to solve business problems.
I built a model that predicts whether a customer would purchase a bank's term sheet or not. The business problem the model seeks to solve is optimization of the bank's marketing effort.
I also built a dashboard with tableau that provides actionable insights from the bank's data.
In this project, I applied my skills in data modeling with PostgreSQL and build an ETL pipeline using Python.
In completing the project, I defined fact and dimension tables for a star schema for a particular analytic focus, and wrote an ETL pipeline that transfers data from files in two local directories into these tables in PostgreSQL using Python and SQL.
I and a team of data scientists built a predictive model to predict likely future sales of pharmaceutical products across multiple stores.
The predictive model was served as an end-to-end product that delivers this prediction and Analysis on the web.
We applied our skills both as machine learning engineers and software engineers to build a web application in Python that allowed users interact with the model over the web
Education
Relevant Course Work: Stylistics, Pragmatics, Critical Thinking and Philosophy
Data Science and Machine Learning (Project Based Training, 10Academy)
current
June 2020 - PRESENT (ending September 2020)
Relevant Coursework:
Build predictive models with Scikit-Learn, PyMc, XGBoost, Catboost, lightgbm etc.
Perform Exploratory Data Analysis
Build Analytics Dashboards with Tableau and Flask.
Build Statistical Models and Deep Learning Models
Relevant Coursework:
Python for Data Wrangling, Descriptive & Prescriptive Analytics, visualization
Descriptive and Inferential statistics for Hypothesis Testing, A/B testing, Probability, Linear and Logistic regression, and sampling techniques in Python for data analytics and building predictive models.
Relevant Coursework:
SQL and No-SQL databases using Python, PostgreSQL, and Apache Cassandra
Data Warehousing and Data Lakes with Spark
Automating Data Pipelines with Apache Airflow
The projects worked on can be found in the project section of my resume.
Python for Scientific Computing and Data Science (WorldQuant University)
completed
January 2020 - March 2020
Relevant Coursework:
Python for Data Wrangling, Descriptive & Analytics, visualization using Pandas, Numpy, Matplotlib
ORM with SQLite & SQLAlchemy, Algorithms & Big O’ Notation
Descriptive & Inferential Statistics
Machine Learning and Statistical Analysis (WorldQuant University)
current (ending December 2020)
September 2020 - till date
Relevant Coursework:
Regression and Classification Models with Scikit-Learn, XGBoost, Catboost, lightgbm, etc.
Pipelines for Data Pre-proccessing and Machine learning models
Natural Language Processing and Sentiment Analysis on Text Data
Descriptive & Inferential Statistics
Deploying Machine Learning models to the Web via Flask and Heroku
Build predictive models with Scikit-Learn, XGBoost, Catboost, lightgbm
Perform Exploratory Data Analysis
Build Neural Networks for Image Detection and Object Recognition
Work Experience
Developed the Back-end of the Machine Learning Operations Platform
Designed and Developed a Machine Learning Orchestration Layer with Java And Kubernetes
Developed a Java Wrapper to Execute Machine Learning codes written in Python
Automated creation/terminations of clusters on AWS with cloud formation
Managed Databases migration in Golang.
Developed Restful services with Blade Framework, Netty and Apache for the MlOps platform.
Semicolon Africa, Lagos, Nigeria
Software Engineer & ML Engineer Trainee
current - (ending December 2020)
September 2019 - PRESENT
Worked on Back-end of Software & Machine Learning Projects
Work an Analytics Project with a group of Data Analysts
Build Predictive models for loan default, customer churn, etc.
Utilized Excel and Microsoft Power BI to perform ETL and Analytics operations on Credit and Investment Data
Prepared and presented reports on analytics findings
