Oluseyi Ajayi

Oluseyi Ajayi Gbagada Lagos Nigeria • --• linkedin.com/in/oluseyiajayi Team Lead: Data Science & AI/ML | Driving $50M+ in Revenue & Operational Efficiency | Expertise in Financial Services, AI/ML Innovation, & Digital Transformation With over a decade of experience in AI, machine learning, and data science, I specialize in leading cross-functional teams to drive innovation and operational optimization across industries like financial services, healthcare, and e-commerce. Currently, as the Team Lead for Data Science & AI/ML at Sterling Financials Holding, I have directed AI/ML strategies that led to N500M+ in revenue growth and improved operational efficiency by 30%. I have successfully developed AIdriven financial products that reduced fraud losses by N100M+, improved credit model accuracy by 50%, and boosted customer engagement by 50%. As a strategic advisor to C-suite executives, I champion AI governance, ensuring regulatory compliance and reducing model risk while driving digital transformation. Professional Experience Sterling Financials Holdings Marina, Lagos, Nigeria. Team Lead, Data Science & AI/ML 05/2023-Present Sterling Financials Holding is a global financial services leader, offering innovative solutions in Commercial banking, wealth management, and retail banking across the world. As the Team Lead for Data Science & AI/ML, I spearheaded the development and deployment of AI/ML solutions to enhance Sterling’s financial services, driving significant business value and technological transformation across the organization. • Directed end-to-end AI/ML strategy, driving N500M+ in revenue growth and optimizing operations by 30% across Sterling’s enterprise, managing a cross-functional team of data scientists, machine learning engineers, and big data specialists, developing and deploying scalable AI/ML solutions leveraging Python, SQL, Spark, Kafka, Snowflake, TensorFlow, PyTorch, and Databricks for real-time processing of 20M+ transactions monthly. • Led the creation of AI-driven financial products, significantly improving customer engagement and operational efficiency: • Liveness Detection Model using CNNs, OpenCV, TensorFlow, reducing fraud losses by N100M+ through enhanced identity verification. • AI Credit Scoring System utilizing XGBoost, LightGBM, alternative data, reducing loan default rates by 25% and boosting credit model accuracy by 50%. • AI Financial Advisory Chatbot (GPT-4, LangChain), automating 70% of client inquiries, increasing engagement by 50% and saving $20M annually in customer service costs via NLP, Hugging Face, and OpenAI API. • NLP-based Query Bot (RAG, FAISS, Pinecone), improving customer service response time by 60% and reducing support workload. • Engineered and implemented MLOps pipelines, reducing model deployment time from 6 weeks to 6 hours, enabling continuous deployment and model performance tracking across AI models using GitHub Actions, Jenkins, MLflow, Kubeflow, Vertex AI, AWS SageMaker. • • • • • • Introduced real-time model monitoring (Prometheus, Grafana, Evidently AI), ensuring high availability and low-latency transactions with Apache Kafka, Flink, Delta Lake, and Snowflake for sub-5ms transaction processing. Architected cloud-native AI infrastructure, migrating workloads to multi-cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML), reducing infrastructure costs by 40%, and implementing serverless computing with Databricks, Snowflake, and BigQuery to streamline large-scale AI and data processing. Led data lakehouse architecture (Delta Lake, Iceberg, Hudi) for better storage scalability and performance across cloud environments. Developed predictive models and advanced analytics for financial risk management and customer analytics: • Led market risk prediction models improving forecast accuracy by 35% using LSTMs, GRUs, and Bayesian methods. • Designed customer lifetime value (CLV) models using reinforcement learning, XGBoost, and time-series forecasting, improving retention by 15%. Drove AI monetization and data democratization, unlocking N200M+ in new revenue, implementing AI-powered recommendation systems that increased cross-sell conversions by 20% via collaborative filtering, matrix factorization, and deep learning techniques. Deployed data mesh architectures and implemented data governance frameworks ensuring compliance with Basel III, CCAR, GDPR, SOC 2, and CCPA. Champion of Responsible AI (XAI) and AI governance, ensuring model fairness, transparency, and ethical standards with bias detection (Fairlearn, AIF360), explainability (SHAP, LIME, Deep SHAP), and regulatory compliance, reducing model risk and aligning AI initiatives with ethical guidelines. Strategic advisor to C-suite executives, leading Sterling HEART Sectors N100M+ digital transformation roadmap, aligning AI investments with business growth and strategic goals. Mentored teams to increase AI-driven automation by 2x, improving model performance by 30%, and boosting productivity by 20% through Agile methodologies and MLOps practices. Developed AI-powered fraud detection system preventing N200M+ in fraudulent transactions using anomaly detection, deep learning, and unsupervised learning, and created Citi’s data-driven decision-making platform, improving executive decision-making, leading to $50M+ in annual savings and 15% greater operational efficiency. Sterling Bank Plc, Marina, Lagos, Nigeria. Senior Data Scientist 02/2020-04/2023 Sterling Bank Plc is a global financial services leader, offering innovative solutions in Commercial banking, wealth management, and retail banking across the world. As the Team Lead for Data Science & AI/ML, I spearheaded the development and deployment of AI/ML solutions to enhance Sterling’s financial services, driving significant business value and technological transformation across the organization. • Pioneered the development of an AI-powered fraud detection system to monitor all customer transactions across Square’s platforms, leveraging machine learning algorithms and ensemble methods to identify and mitigate fraudulent activity, reducing fraud by 40% and ensuring enhanced transaction security. • Architected and deployed a comprehensive Spend Analytics Tool utilizing Python, SQL, and Pandas to extract actionable insights from customer transaction data, resulting in a 15% improvement in customer retention and enabling more targeted, data-driven business strategies that directly impacted revenue growth. • Drove key data monetization initiatives, including product recommendation systems, dormancy analysis, and lead generation models, increasing customer engagement by 20% • • • • • and driving N200M in incremental revenue through highly personalized, data-driven offerings. Developed a Social Media Analytics platform employing NLP, sentiment analysis, and topic modeling for performance tracking across Twitter, Instagram, and Blogs, optimizing Square’s marketing strategies and boosting social media ROI by 25%. Led a comprehensive pricing optimization project across E-channel platforms, utilizing A/B testing, machine learning, and market elasticity models to refine pricing strategies, resulting in a 12% increase in revenue and improved competitive positioning in the market. Engineered and implemented a Customer Lifetime Value (CLV) model using time-series forecasting, regression analysis, and machine learning techniques, driving 30% improvement in marketing ROI and enabling the design of tailored campaigns for highvalue customers. Spearheaded data democratization efforts across the organization, establishing real-time analytics access for cross-functional teams, resulting in 20% productivity increase and empowering decision-makers with actionable insights for strategic planning. Led the design and deployment of an AI-powered chatbot for Risk Management, utilizing natural language processing and conversational AI to automate key processes, reduce manual workload by 50%, and enhance real-time risk analysis, streamlining operations and improving decision-making. Fidelity Bank Plc, VI, Lagos Nigeria Data Scientist / AI Engineer 08/2018-01/2020 Fidelity Bank, a financial institution, leverages advanced technology to drive innovation in banking. As a Data Scientist and AI Engineer, I led AI/ML initiatives that optimized customer insights, automated operations, and improved financial performance, resulting in 25% improved operational efficiency and $5M in incremental revenue. • Developed and deployed advanced predictive models for customer propensity, churn prediction, and credit scoring using machine learning techniques (e.g., logistic regression, random forests, XGBoost), improving customer retention by 10% and refining credit assessments, boosting approval accuracy by 20%. • Created a Next Best Offer Engine by integrating credit scoring models with recommendation algorithms and collaborative filtering, driving an 18% increase in cross-sell conversions and enhancing revenue by N75M+ through personalized product recommendations. • Automated manual processes through robotic process automation (RPA) and machine learning, resulting in a 30% reduction in processing time and cost savings across departments by streamlining key workflows and increasing operational efficiency. • Developed Virtual Assistants (Chatbots) using Natural Language Processing (NLP) and deep learning techniques, decreasing call center volume by 20% and improving customer satisfaction by 15% through real-time, AI-powered interactions. • Optimized ETL pipeline with real-time machine learning models to ensure high-quality data extraction, transformation, and loading, enabling enhanced data accessibility for business decision-making and supporting data-driven solutions bank-wide. • Led social media analytics using sentiment analysis and NLP techniques, boosting cross-sell conversions by 12% and proactively driving customer engagement through targeted campaigns and product offerings. Igbinedion University Teaching Hospital Okada, Edo, Nigeria. Data Analyst 12/2015-05/2018 Igbinedion University Teaching Hospital, a leading healthcare provider, is dedicated to delivering innovative patient care through strategic initiatives. As a Data Analyst, I leveraged datadriven solutions to optimize operations, support decision-making, and enhance patient care outcomes, delivering measurable business value across the organization. • Spearheaded data analysis for patient care improvements, resulting in optimized workflows, reduced patient waits times, and an overall improvement in patient outcomes by 15%. • Collaborated with cross-functional teams (sales, admin, exams, and records) to develop and execute a data-driven marketing strategy, aligning company goals and enhancing patient engagement by 15% through targeted healthcare service initiatives. • Led the creation of business architecture by gathering, analyzing, and documenting client requirements, including scope, processes, risks, and alternatives, ensuring alignment with development teams to drive strategic healthcare projects. • Reconciled and ensured the accuracy of client data, identifying discrepancies, and refining business rules to improve the overall data quality and facilitate accurate decision-making, ensuring operational efficiency across multiple departments. • Developed and maintained comprehensive business requirements that aligned with both functional and technical objectives, enabling streamlined execution of healthcare initiatives and driving improvements in operational workflows. • Created actionable data models and process diagrams to present business requirements to non-technical stakeholders, resulting in improved collaboration between teams and better decision-making at the executive level. • Initiated data-driven analyses that contributed to process optimization, reducing operational inefficiencies by 20% and improving resource allocation within healthcare teams, ultimately improving service delivery. • Streamlined the reporting process by automating key data collection and reporting functions, enabling timely and accurate business insights that improved operational response times by 25%. • Supported healthcare initiatives by providing key insights through detailed data analysis, driving improvements in patient care and reducing operational bottlenecks, which led to a 10% increase in patient satisfaction. IITA, Ibadan, Oyo Nigeria. IT Data Engineer 12/2011-09/2013 At IITA Ibadan, Nigeria, I contributed as an Intern Data Engineer by assisting in the development and optimization of scalable data infrastructures that supported operational efficiency and enhanced data-driven decision-making across various departments. My efforts played a key role in streamlining data processes and improving outcomes, both in the agricultural sector and within the institute’s operations. • Assisted in streamlining reporting processes, improving both the efficiency and accuracy of agricultural data, contributing to a 25% increase in operational efficiency across research and operational teams. • Helped develop and implement scalable data architectures that aligned with business needs, enabling better cross-department integration of research data and improving workflow efficiency by 15%. • • • • • • Collaborated with cross-functional teams (research, field operations, admin, and data analytics) to align technical execution with organizational goals, enhancing communication and ensuring consistent implementation of data strategies. Ensured the accuracy and integrity of client data by identifying and resolving discrepancies, ultimately improving the reliability of business intelligence and supporting more informed decision-making. Assisted in the design and optimization of ETL processes, improving the extraction, transformation, and loading of data from various sources to ensure timely access to crucial insights, contributing to a 20% reduction in reporting time. Supported the engineering and automation of data pipelines that enabled real-time data reporting and analytics, allowing for faster insights and more agile decision-making across departments. Contributed to the creation of business requirements documents and aligned them with functional and technical specifications, ensuring smooth project execution in line with research and institutional standards. Communicated technical data models and process flows to non-technical stakeholders, ensuring understanding and fostering collaboration across research teams. Skills Technical Skills • Programming Languages: Python, SQL, Java, R, JavaScript, Shell Scripting • Machine Learning & AI: Deep Learning, NLP, Computer Vision, Time Series Forecasting, Reinforcement Learning, Ensemble Learning, Clustering, Anomaly Detection, XGBoost, LightGBM, Random Forest, SVM, KNN, Logistic Regression • Data Engineering & ETL: Apache Kafka, Apache Flink, Apache Spark, Snowflake, Delta Lake, ETL Pipelines, Data Warehousing, AWS SageMaker, GCP Vertex AI, Azure ML, Databricks, BigQuery • Cloud & Infrastructure: AWS (EC2, S3, RDS, SageMaker), GCP (Vertex AI, BigQuery, Cloud Storage), Azure (Azure ML), Kubernetes, Docker, Terraform, Serverless Computing, MultiCloud Architecture • MLOps & Automation: GitHub Actions, Jenkins, MLflow, Kubeflow, Vertex AI, Prometheus, Grafana, CI/CD Pipelines, Real-time Model Monitoring • AI & Deep Learning Frameworks: TensorFlow, PyTorch, Keras, OpenCV, Hugging Face, GPT-4, LangChain, FAISS, Pinecone • Data Analytics & Business Intelligence: Pandas, Numpy, Scikit-learn, Tableau, Power BI, Matplotlib, Seaborn • Big Data Technologies: Apache Hadoop, Apache Hive, Apache Pig, Spark Streaming, Flink, Hudi, Iceberg • Data Visualization: Tableau, Power BI, Data Studio, Dash • AI Governance & Responsible AI: Fairlearn, AIF360, SHAP, LIME, Deep SHAP • Data Modeling: Time Series Forecasting, Bayesian Inference, Market Risk Prediction, Customer Lifetime Value (CLV), Sentiment Analysis, Query Bots Leadership & Strategic Skills • Team Leadership: Leading cross-functional teams, mentoring data scientists, machine learning engineers, and data engineers. • • • • • Business Strategy: Driving AI/ML product strategy, data-driven decision-making, AI monetization, and business process optimization. Stakeholder Management: Engaging with C-suite executives, advising on digital transformation roadmaps, and aligning AI strategies with business objectives. Agile & Lean Methodologies: Agile frameworks, Scrum, Kanban, continuous improvement, and collaboration. AI Governance & Compliance: Basel III, CCAR, GDPR, SOC 2, CCPA compliance, and ethical AI. Business Process Optimization: Identifying automation opportunities, increasing operational efficiency, and reducing costs. Industry-Specific Expertise • Financial Services: Credit Scoring, Fraud Detection, Customer Segmentation, Pricing Optimization, Predictive Analytics, Risk Management. • Healthcare: Patient Care Optimization, Healthcare Analytics, Healthcare Data Compliance, Business Intelligence in Healthcare, Patient Outcomes Improvement. • E-commerce: Customer Retention, Product Recommendations, Sentiment Analysis, Personalization, Social Media Analytics. • Cryptocurrency: Blockchain Analytics, Cryptocurrency Fraud Prevention, Transaction Monitoring, Cryptocurrency Pricing Models. Education Bachelor of Science in Computer Science, (2011 -2015), Bowen University Iwo, Osun Nigeria