- Location
- Calgary, Alberta, Canada
- Bio
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I am a passionate and detail-oriented data scientist with a vision to make outstanding contributions to e-commerce, market predictions, healthcare analysis and disease modelling. I previously worked a postdoctoral scientist at the US National Institutes of Health, where developed an innovative data science-driven research initiative on rare variants associated with clonal hematopoiesis. My skills encompass a wide range of programming languages and tools, including Python, R, SQL, and Linux. I have expertise in data visualization, Tableau, Scikit Learn, data cleaning, supervised and unsupervised machine learning, deep learning, and natural language processing (NLP). I have hands-on experience with big data, particularly in genome sequence analysis using GATK for variant calling and analysis. I am well-versed in using Docker and AWS for data science applications.
My educational background includes a Diploma in Data Science from LightHouse Labs (Canada) and a PhD in Bioinformatics. My research work has received considerable recognitions and awards. For instance, I was awarded the US National Institutes of Health Emerging Global Leader Award and the Career Development Fellowship Award from the European Union. I am excited about the opportunity to bring my skills, experience, and passion for data science to your organization. I am eager to contribute to your innovative data-driven projects.
- Resume
- Kolapo Oyebola Resume.pdf
- Portals
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Toronto, Ontario, Canada
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- Categories
- Data visualization Data analysis Data modelling Machine learning Data science
Skills
Achievements
Latest feedback
Individual endorsement
Kolapo took on the critical task of Enhanced Vulnerability Testing, producing a thorough guide that addressed blockchain, smart contract, and QR code security challenges. He displayed strong analytical skills and a keen attention to detail, identifying potential vulnerabilities and recommending mitigation strategies. Kolapo’s proactive approach and ability to integrate feedback made him an invaluable contributor to the team
Learner feedback
Team feedback
Recent projects
Mobile App Data Analytics Project
We are looking for learners to help analyze our mobile app datasets to draw helpful insights. From this analysis, we hope to gain insights that will will drive our product roadmap. These insights will be directly related to business outcomes and help us shape how we need to evolve our business in the future. The scope includes assessing existing and proposed data sources / datasets against Key Performance Indicators to establish current state and gaps; and implement analysis solutions to address gaps. Learners will benefit from experience working with a mobile app team to learn about the KPIs and data sources--such as Google Play, The Apple App Store, Google Firebase/Analytics, and relevant to the mobile app industry; and the data [EMPLOYERS: please expand on the above and share any details as to what your project scope entails, and why a learner would benefit from applying to your project - the more information the better!]
VISS ICT Ignite - Cyber Security Project
To comprehensively enhance the security posture of our company's Crypto OTC desk operations, ensuring the robust protection of sensitive data, systems, and networks. Company Overview for Context: We are a FINTRAC-licensed organization specializing in cryptocurrency Over-The-Counter (OTC) desk services. We prioritize the security and integrity of our operations to safeguard our clients' trust and comply with regulatory requirements. Learner Opportunity: By participating in this project, learners will have a unique opportunity to apply their freshly acquired cybersecurity skills in a real-world, regulated financial environment. They will work closely with our team to identify vulnerabilities, design and implement security enhancements, and contribute to the ongoing protection of our Crypto OTC desk operations. Additionally, learners will: Design, implement, and test blockchain solutions, including smart contracts and NFTs , for authenticating oil and gas transactions. Integrate QR code verification as a complementary tool to certify authenticity and improve usability for stakeholders unfamiliar with blockchain. Tasks and Activities for Learners: 1. Security Assessment: Conduct vulnerability scans and risk analyses on our Crypto OTC desk's infrastructure and workflows. Identify potential entry points for cyber threats and prioritize them based on risk. Blockchain Security : Assess the risks associated with smart contract deployment for oil and gas trading, identifying potential vulnerabilities in the contract code and blockchain network infrastructure. 2. Security Architecture Enhancement: Design and propose improvements to our current security architecture. Ensure alignment with industry best practices and FINTRAC regulatory requirements. Smart Contract Integration : Develop an architecture that integrates smart contracts into the Crypto OTC desk’s workflow for the oil and gas transactions, ensuring secure interaction between blockchain elements and our infrastructure. QR Code Verification Design : Develop a process to generate and link QR codes to blockchain transaction records, making them accessible via blockchain explorers or secure off-chain platforms. 3. Implementation and Testing: Collaborate with our team to implement recommended security measures. Perform thorough testing to validate the effectiveness of the new security configurations. Smart Contract Execution Testing : Deploy smart contracts for oil and gas transactions in a testnet environment and verify proper execution of command chains, payment release, and title transfer automation. QR Code Testing : Ensure QR codes correctly link to blockchain-verified transaction summaries, testing both accessibility and security. 4. Monitoring and Incident Response Planning: Establish a monitoring plan to detect potential security breaches. Develop an incident response plan tailored to our Crypto OTC desk operations. Blockchain Monitoring : Implement tools for real-time monitoring of blockchain interactions, ensuring transaction integrity and detecting anomalies in smart contract execution. QR Code Fraud Prevention : Include monitoring for QR code misuse or tampering, ensuring that each code links only to its intended blockchain record. 5. Documentation and Knowledge Transfer: Maintain detailed records of all activities, findings, and solutions implemented. Conduct a knowledge transfer session with our team to ensure seamless ongoing management. Blockchain Documentation : Provide detailed explanations of the smart contract design, NFT integration processes, and blockchain-specific incident response protocols. QR Code Workflow Documentation : Create user guides for generating and validating QR codes, tailored to oil and gas industry stakeholders. Deliverables to Achieve the Project Goal: 1. Comprehensive Security Assessment Report Identify vulnerabilities and blockchain-specific risks. 2. Enhanced Security Architecture Design Document Include blockchain integration design, smart contract workflows, and QR code verification. 3. Implementation and Testing Report Verify the effectiveness of security enhancements, blockchain deployments, and QR code integration. 4. Monitoring Plan and Incident Response Procedure Document Define specific steps to handle smart contract, NFT, and QR code-related incidents. 5. Final Project Presentation and Knowledge Transfer Session Summarize results and ensure the team understands blockchain, QR code workflows, and cybersecurity integrations. Expected Outcomes: Upon project completion, we aim to have significantly enhanced the security of our Crypto OTC desk operations, ensuring the protection of sensitive data and compliance with regulatory requirements. In addition, the integration of smart contracts, NFTs, and QR codes into the oil and gas transaction process will establish a new standard for securing commodity trades. Learners will gain hands-on experience with: Managing a cybersecurity project within a regulated financial sector environment. Designing, deploying, and securing blockchain solutions for industrial applications. Bridging technical and non-technical stakeholders through QR code integration.
Education
Diploma, Data Science
LightHouse Labs
August 2023 - November 2023
PhD, Bioinformatics and Parasitology
University of Lagos
December 2012 - January 2016
Personal projects
Machine_Learning_Model_Predicting_Diabetes
October 2023 - October 2023
Tools: Python, Matplotlib, Scikit Learn
Algorithms: LogisticRegression, SVC and RandomForestClassifier
Goal: used supervised learning techniques to build a machine learning model to predict whether a patient has diabetes or
not, based on certain diagnostic measurements.
Dataset: Diabetes dataset
Results: Logistic Regression model is the best model for this prediction since it has a maximum accuracy_score of 0.79.
Car insurance claim prediction
September 2023 - September 2023
Tools: Python, Matplotlib, Scikit Learn
Algorithm: Logistic Regression Model
Goal: To predict whether a customer will make a claim on their car insurance during the policy period.
Dataset: Car insurance claim predictor.
Results: 'Age' and 'driving experience' had the highest accuracy scores for prediction
Transforming and analyzing data using SQL
August 2023 - August 2023
Tools: PostgreSQL
Goal: determine revenue by product as well as data on how each visitor to the site interacted with the products
Dataset: ecommerce database
Results: generated entity relationship diagram (ERD) for the database