Javier Saez Gallego
Verified Expert in Engineering
Data Scientist and Developer
Javier是一位充满激情的数据科学家，他构建了数据驱动的软件产品，并帮助组织将数字转化为最佳决策. With a multidisciplinary background, 他分析了高维数据集，并建立了机器学习模型——从研究阶段到实施阶段. Javier is careful, very organized, 对计划一丝不苟，始终专注于交付正确的解决方案.
Portfolio
Experience
Availability
Preferred Environment
Linux, Docker, Git, Python, Azure, Amazon Web Services (AWS)
The most amazing...
...我所做的事情是开发一个销售工程师用来计算风力涡轮机保修的应用程序.
Work Experience
Data Scientist
Reforestum
- 开发了使用卫星图像监测森林区域的深度学习模型. 最终目标是监测森林状况并实时计算碳储量.
- Implemented a back end that performs ETL, machine learning modeling, and serves the results via an API.
- Visualized GIS results via Mapbox.
- Trained and deployed machine learning models in AWS.
Data Scientist Consultant
Minsait
- 识别机器学习模型可以为客户带来价值的潜在商业案例.
- Participated in the research, development, 以及为欧洲最大的银行之一实施自动取款机的预测性维护模型.
- Developed dashboards and interactive graphs.
Data Scientist
TecDeSoft
- 利用现有客户的可用数据创造业务价值，专注于数据驱动的操作.
- 对厂区进行预测性维护，对水电站进行优化调度.
- 教我的同事们数据科学和机器学习的原理.
Data Scientist
Siemens Gamesa
- Developed a framework consisting of a database, an app, 还有一个仪表盘，让用户预测风力涡轮机的性能.
- 分析测量数据，发现与预期行为可能存在的偏差.
- 从多维数据集中提取有意义的信息.
- 以简洁明了的方式将结果和统计术语传达给电气工程师和销售人员.
- Read, studied, and kept up to date with current ISO standards.
- Quantified the risk of different warranty strategies.
PhD Candidate
Technical University of Denmark
- 基于随机优化技术，建立了不确定条件下的决策模型.
- 构建了一种基于逆优化技术和机器学习原理的新型预测建模框架.
- 广泛使用R进行数据处理，并使用GAMS-CPLEX构建优化模型.
- 使用云计算框架来并行计算.
- 在里斯本国际会议上介绍研究课题和成果, Glasgow, and Philadelphia.
- Published four articles in well-ranked journals.
- 在加州大学做了四个月的访问学者.
Experience
Squirrel Problem
http://jsaezgallego.com/GlobCover_maps_squirrel/The answer is: obviously not. But, another question arises, 这个问题不太容易回答:如果一只松鼠必须从西班牙北部走到南部, 尽可能少地接触地面:它会朝哪个方向走?
The answer is not trivial, and it is answered here!
The project consisted of the following steps:
1. Download data from the internet. 该数据由GIS信息组成，用于确定一块土地是否为森林, a river, a man-made construction, and so on.
2. Create a path matrix. The squirrel takes one step at a time. 就栅格图而言，这意味着我们只能从相邻像素到达每个像素. Think of it as a huge spare matrix.
3. Optimize the path. 计算从西班牙顶部到底部的最短路径. 每个部分的成本是像素值，所以穿过森林不需要任何成本，而任何与水有关的东西都不可能穿过.
4. Visualize the solution as an interactive map.
Notification Bundler
http://github.com/jsga/bundle_notificationsAvatar Generation with AI
http://infiniteavatarai.comShowYourLocalStripes
http://showyourlocalstripes.com/Bird Audio Recognition
http://www.spinysoftware.com/chirpomatic/Skills
Languages
Java, Python, R, JavaScript, SQL, GAMS
Frameworks
Spring, Flask, RStudio Shiny
Libraries/APIs
Node.js, Pandas, Plotly.js, PyTorch, Keras, Ggplot2, TensorFlow, React, Vue
Paradigms
DevOps, Data Science
Other
Software Development, Machine Learning, Data Analysis, Dashboard Design, Operations Research, Mathematical Modeling, Computer Vision, Algorithm Development, Artificial Intelligence (AI), Optimization, Dash, FastAPI, Audio Processing, APIs
Tools
Git, MATLAB, Plotly, CPLEX, Dplyr
Platforms
Linux, Docker, Kubernetes, Amazon Web Services (AWS), Jupyter Notebook, Mapbox, Amazon EC2, Azure, AWS IoT
Storage
Amazon S3 (AWS S3), PostgreSQL
Education
Master's Degree in Mathematical Modeling
Technical University of Denmark - Copenhagen, Denmark
Master's Degree in Statistics and Operations Research
University of Valladolid - Valladolid, Spain
Bachelor's Degree in Statistics and Operations Research
University of Valladolid - Valladolid, Spain
Certifications
Deep Learning
Deeplearning.ai via Coursera
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