Samuel Surulere

WORK HISTORY

EDUCATION

ABOUT SAMUEL SURULERE

I am an experienced Data Scientist with a strong academic and teaching background. My transition from academia to data science was driven by a passion for solving problems, which I found limited in theoretical research. Today, I combine my mathematical knowledge with both traditional and advanced machine learning techniques to deliver impactful, data-driven solutions. I specialize in transforming complex data into actionable insights that help businesses optimize decision-making and drive business growth.Some of my core competencies are outlined below:Traditional Machine Learning Models - Proficient in building predictive models (classification, regression, customer segmentation, clustering), forecasting, customer churn rate, recommendation systems.Programming, Data Preprocessing & Visualization - Skilled in Python, R, SQL, Tableau, Matplotlib, and Seaborn. ML libraries like NumPy, Pandas, Scikit-Learn, SciPy, PyTorch, TensorFlow, Keras.MLOps, Cloud Technologies & Deployment - Experience with MLflow, Jenkins, Docker, Prometheus, Grafana, deploying models via CI/CD pipelines like CircleCI, deploying models as API endpoints/microservices using Flask, FastAPI or through UIs like Streamlit, Gradio and deploying models on cloud platforms like Railway, Cloud66 (used as a wrapper on cloud machines).NLP & Generative AI - Proficient in NLP frameworks like NLTK, spaCy, HuggingFace, building production-grade RAG architectures, finetuning open-source LLMs using unsloth and PEFT techniques like LoRA and QLoRA to build LLM-based solutions. Experienced in deploying LLM apps using transformers, vLLM (for model serving/inference) & Ollama. Fluent in employing tools from the LangChain ecosystem. Built agentic RAG solutions using LangGraph.Soft Skills & Cross-functional collaboration - Mentored graduate students, collaborated with colleagues on research, fast learner, adaptive thinker, monitored & managed research projects timelines. Collaborated with developers, UI/UX designers & project managers to deliver ML projects.Agile Environment - Familiar with tools like Shortcut for organizing & executing ML projects efficiently.With a growing curiosity about using traditional and advanced machine learning tools to solve business problems, I am always looking forward to growing expertise in driving innovative business solutions.