I am Daniel Coronel, a Senior Data Scientist based in Oslo, Norway, with a background in geosciences 🪨. I have 5+ years of experience building and deploying end-to-end machine learning solutions, with a proven track record delivering production ML systems for clients in finance, healthcare, O&G, aquaculture, and construction. I am passionate about working with multi-scale and multi-dimensional data, and I thrive in fast-paced, experimental environments where quick iteration and practical problem-solving drive results.
My main interests are:
- MLOps & end-to-end ML systems
- Computer vision 👀
- Geospatial data-science 🌎
- Quantitative seismic interpretation 💥
- Visualization 🔍
- GenAI applications
| Area | Tools |
|---|---|
| ML & Data Science | PyTorch, Transformers, Scikit-learn, Pandas, NumPy, Xarray, Dask, Matplotlib |
| MLOps & DevOps | Docker, CI/CD pipelines, MLFlow, Hydra, AWS SageMaker, AzureML, git |
| Cloud Platforms | Azure (primary), AWS |
| GenAI | LlamaIndex, smolagents |
Senior Data Scientist — Telenor Norge (Business) (Feb. 2026 – Present, Oslo, Norway)
- Building recommendation systems and agentic engines to improve sales processes.
Senior Data Scientist — Crayon Consulting (Feb. 2023 – Jan. 2026, Oslo, Norway)
- Delivering data science projects for customers across different industries: social media, aquaculture, finance, healthcare, and O&G.
- Implementing end-to-end ML solutions in computer vision, time series, synthetic data generation, structured data, and LLMs.
- Implementation of PoCs and MVPs for GenAI use cases in the construction industry and contract analysis.
Geo-Data Scientist — RagnaRock Geo (Aug. 2020 – Oct. 2022, Oslo, Norway)
- Part of a team delivering machine learning workflows and solutions for E&P companies.
- Responsible for the ingestion of subsurface data and its preparation for machine learning workflows.
- Implemented data science pipelines and ML models for regression and image segmentation problems.
- Generated back-end interaction with cloud applications to initialize, interact, and visualize workflows.
Geoscientist — RagnaRock Geo (Jan. 2020 – Jul. 2020, Trondheim, Norway)
- Led geoscience quality control of labeled data for training machine learning models.
- Participated in the development of a conceptual model for an ML-guided stratigraphic interpretation tool.
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F3 👷: Experimental project to learn about parsing different subsurface data formats. Most of the parsers read OpendTect formats. Additionally, I created some small scripts to create seismic, horizons and well objects and the ability to interact with them.
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FWI: Numerical methods course project from my Master's degree. We work on a seismic inversion problem to recover a velocity model from shot gathers. Here, we put in practice solving differential partial equations (Acoustic wave equation) and optimization algorithms to solve the inverse problem.