Daniela Risco

Data scientist, currently doing an MSc in Data Science at the University of Bristol. I use machine learning and AI to solve real‑world problems, from gas‑plant maintenance to museum collections.

See selected work danielarb.99@outlook.com

Ripples, generated live in WebGL. Move your cursor over it.

/* Selected work */

Machine learning, analytics and AI products. Web and app design is further down.

MoodMuse

MoodMuse showing a painting recommended from a journal entry
When
2025
Built at Google’s AI in Action hackathon
Stack
Python, FastAPI, Vertex AI, BLIP‑2, OpenAI API, MongoDB Atlas

You write how you feel, and MoodMuse finds a painting that matches it. I captioned about 15,000 artworks from The Met’s open collection with BLIP‑2 on Vertex AI, enriched each one with emotion and colour metadata in MongoDB Atlas, and matched them against the mood detected in the user’s text. The API runs on FastAPI in Cloud Run.

Maintenance analytics for Peru LNG

Anonymised maintenance dashboard
When
2024 - 2025
APTIM, Melchorita LNG plant
Stack
Power BI, DAX, SQL Server, Power Automate, SharePoint, Azure

I built and rolled out the maintenance dashboard for the Melchorita plant and analysed sensor data from gas plants with an international engineering team. I also automated work‑order failure reporting with Power Automate on SharePoint, and applied generative AI in the cloud to maintenance work.

Pathora

Pathora showing a walking route through Barranco on a map
When
2025
Entry for the Google Maps Platform Awards
Stack
Python, FastAPI, GPT‑4, Places API, Distance Matrix API, Firebase

Describe the day you want, like “museums and cafés in Barranco, nothing rushed”, and Pathora returns a route. GPT‑4 turns the request into constraints on time, energy and budget; the backend picks top‑rated places from Google Maps and lays them out on an interactive map you can save or share.

Music genre classification

PCA projection of tracks coloured by genre
When
2025
Machine learning notebook
Stack
Python, scikit‑learn, pandas, seaborn

Classifies tracks into genres from audio features such as tempo and vocal presence. PCA compresses the feature space, logistic regression predicts the genre, and the trained model then labels the part of the dataset that had no genre. Accuracy held up with far fewer dimensions.

/* About */

I’m a Data Scientist working at the intersection of data, AI and technology, currently based in Bristol.

At APTIM, I’ve worked with operational and sensor data from industrial environments, building data solutions for areas including Human Resources, Occupational Health and Logistics. I’m now also exploring how AI can support planning and decision-making, including a project focused on extracting and connecting information from SAP R/3 maintenance data.

My curiosity has taken me from industrial data to AI, from building digital products to experimenting with ideas of my own — including MoodMuse, a project that started with a painting.

Core Technologies
Python (Pandas, Scikit‑Learn, TensorFlow, Keras), R, SQL
Machine Learning
EDA, Feature engineering, Model Evaluation, Hyperparameter tuning, Supervised Learning (Linear Regression, Decision Trees, Random Forests) and Unsupervised Learning (K-Means, Hierarchical Clustering)
Cloud and AI services
Azure (Azure ML), Google Cloud (Vertex AI), OpenAI API, MongoDB Atlas, Firebase
Visualization
Looker, Power BI, Tableau
Automation
Power Automate, PowerApps, GitHub Actions
Building
HTML, CSS, JavaScript, FastAPI, Flutter

/* Experience */

AI & Data Science Consultant

Sep 2026 - Present, Remote

  • Developing a Generative AI solution with Azure for intelligent maintenance work-order planning across two industrial plants operated by Pluspetrol. Leveraging historial SAP R/3 maintenance data to identify patterns, generate AI-driven recommendations, and support planning.

Data Analyst

Oct 2024 – Aug 2026, Lima, Peru

  • Built Power BI dashboards for the Human Resources, Occupational Health and Logistics teams.
  • Analysed sensor data from gas plants alongside the international team.
  • Implemented the maintenance dashboard for the Melchorita plant (Peru LNG).
  • Automated work‑order failure reporting with Power Automate and SharePoint.

/* Credentials */

Education

  1. 2026 – 2027 MSc Data Science University of Bristol
  2. 2015 - 2020 BSc Industrial and Systems Engineering University of Piura

Certifications

  1. AZ‑900 Microsoft Certified: Azure Fundamentals Cloud concepts, core Azure services, security, governance and pricing. Verify
  2. PL‑300 Microsoft Certified: Power BI Data Analyst Associate Data modelling, DAX and M, visualisation and interactive dashboards. Verify
  3. GitHub GitHub Actions CI/CD pipelines, automated tests, builds and deployments. Verify
  4. GitHub GitHub Foundations Version control, Git workflows and collaboration on GitHub. Verify

Courses

  1. Jun 2026Forward ProgramMcKinsey & Company
  2. Nov 2025CS50: Introduction to Computer ScienceHarvard University
  3. Sep 2025Deep Learning SpecializationDeepLearning.AI
  4. Jul 2025Machine Learning SpecializationDeepLearning.AI
  5. Jan 2025Product Management for AI and Data Science365 Data Science
  1. Jul 2025AI for EveryoneDeepLearning.AI
  2. Jul 2025Business Strategy: Competitive AdvantageWharton, Coursera
  3. Mar 2025Flutter and DartUdemy
  4. Jan 2025Data Privacy and Protection LawUniversity of Pennsylvania
  5. Jan 2025ChatGPT for Data Science365 Data Science
  6. May 2022Energy Innovation and Emerging Technologies ProgramStanford University
  7. Sep 2020IBM Data Science Professional CertificateIBM, Coursera

Talks and teaching

  1. Ago 2026 Talk: Power BI for projects, business, and professional management IEEE Young Professionals
  2. Jul 2026 Volunteer for disaster response UNV, Humanitarian OpenStreetMap Team
  3. Sep 2025 Volunteer Scratch teacher IE Enrique Nerini
  4. Jul 2025 Volunteer office software teacher Pachacútec Institute
  5. Oct 2024 Talk: Data science in action, innovation and opportunities for young professionals IEEE Young Professionals

/* Web and app design */

I also design and build websites and apps for clients and for fun.

Get in touch

I’m happy to talk about data science roles and projects.