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

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.

• 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.

• 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.