Leo C.

Data Scientist & Machine Learning Engineer specializing in production-ready machine learning systems that solve practical problems. I’ve delivered over $2.5M in measurable annual savings by designing, deploying, and unblocking machine learning solutions across Manufacturing, Recruitment, Sales, and Marketing. I adapt data pipelines, models, and evaluation strategies to fit the needs and goals of each business function. Core Expertise: 📌 End-to-end machine learning systems 📌 Data pipelines for robust workflows 📌 Domain-tailored solutions 📌 MLOps aligned with existing workflows 📌 Strategy for ML, data, and platforms Project Highlights: 📈 Built ML capability from zero over 5.5 years at a major steel plant as its first Data Scientist. Scaled the team to 5 people by hiring 2 Data Scientists and 2 Data Engineers, and established an MLOps way-of-working that increased project output by 3.5x. 📈 Removed a key blocker to ML integration by aligning 5 departments around a shared analytics platform, enabling reliable data visualization and model validation — resulting in broad adoption and $1.5M in annual cost savings. 📈 Revived a stalled machine learning model by developing a custom evaluation algorithm, achieving $600K in annual cost savings. 📈 Developed and maintained an end-to-end ML-based image recognition system for a steel plant, resulting in $500K in annual cost savings. 📈 Designed and implemented a data pipeline that aggregated and transferred over 2,300 sensor values to a forecasting model, enabling predictive maintenance for a plate furnace. What I Bring to Every Project: 🔷 Adapting quickly across domains, with a proven ability to learn new fields fast 🔷 Simplifying complex concepts so decision-makers can act with confidence 🔷 Collaborating effectively in cross-functional teams 🔷 Applying both deep and broad expertise in data science and machine learning 🔷 Ensuring clarity and alignment throughout the project 🔷 Delivering well-documented code and smooth handover for long-term maintainability Technical Skills: ❇️ Machine Learning Types (Classification, Regression, Image Recognition, Ranking Models) ❇️ Machine Learning Development (scikit-learn, PyTorch, XGBoost, SHAP) ❇️ Data Engineering (Pandas, SQL, Apache Airflow, Apache Iceberg, Trino, dbt, Databricks) ❇️ Deployment (Docker, FastAPI, Github Actions) ❇️ Data Visualization (Matplotlib, Seaborn, Interactive Dashboards, Grafana) ❇️ Python (Pandas, Numpy, SciPy) I care deeply about delivering practically useful solutions that are capable of delivering value for the long-term. I achieve this by respecting domain knowledge, building reliable systems, and keeping a clear line of sight to business value. I’m focused on projects where my experience can make a meaningful impact and where I can ensure that the delivery meets a high standard. If you’re looking for an experienced Data Scientist who focuses on business value, not just code, I’d love to explore how we can unlock value from your data.