Othmane Kounima

Data Scientist | ML Engineer | Big Data & Product Analytics

I am a Data Scientist who believes that the most powerful models are the ones that solve real-world product problems. From the precision-heavy world of pharmaceutical research to the high-scale environment of telecommunications, I specialize in building end-to-end data solutions that transform raw, terabyte-scale data into strategic business assets.

What I bring to the table:

Big Data Engineering: I have a proven track record of handling terabytes of daily data, architecting pipelines on Databricks using PySpark, SQL, and Scala. I am proficient in modern MLOps practices, including Databricks Asset Bundles (DABs) and CI/CD integration.

Predictive Modeling & Research: I enjoy solving complex data challenges, such as benchmarking ML imputation methods for missing pharmaceutical data or building Anomaly Detection (Isolation Forests) and Time-Series churn models for telecom products.

Product-Driven Insights: I bridge the gap between technical data and product strategy. I have built pattern detection engines to analyze API behavior and designed automated Tableau dashboards that empower Product Managers to make data-backed decisions.

Technical Toolkit:

Languages: Python, SQL, Scala, R.

Data Engineering: Apache Spark (PySpark), Databricks, ETL/ELT, Avro.

ML/Stats: Supervised/Unsupervised Learning, Pattern Recognition, Time-Series, Statistical Benchmarking.

Visualization: Tableau, PowerBI, Matplotlib/Seaborn.

I am always eager to connect with fellow data enthusiasts and product innovators. Let’s talk about how we can turn complex datasets into clear growth opportunities.