Nicolas Keller, Data Scientist and Developer in Madrid, Spain
Nicolas Keller

Data Scientist and Developer in Madrid, Spain

Member since October 1, 2019
With a strong mathematical background (a master's degree in mathematics), Nicolas is a passionate data scientist who can contribute the ideal combination of machine learning knowledge, practical programming skills, and a problem solving and analytical mindset to a project. He has a demonstrated history of transforming business problems into data-driven solutions and recently has worked as a data scientist at the global insurance company, Allianz.
Nicolas is now available for hire

Portfolio

Experience

Location

Madrid, Spain

Availability

Part-time

Preferred Environment

Jupyter Notebook, RStudio, Git, Linux

The most amazing...

...thing I've coded was an R package to predict life insurance claims based on individual characteristics. It is a novel approach going beyond the status quo.

Employment

  • Data Scientist

    2020 - PRESENT
    Moneyhub
    • Implemented and productionized a personalized machine learning algorithm to classify transaction data using the AWS SageMaker and Lambda infrastructure.
    • Detected trends in the behavior of customers and created frequent reports to present the results which have been published regularly on the company's website.
    • Completed various data analyses and POCs to answer requests from the business using a combination of SQL/Python for the backend and Jupyter Notebooks and Plotly to present findings.
    Technologies: Amazon Web Services (AWS), Natural Language Processing (NLP), Machine Learning, Plotly, Jupyter Notebook, SQL, Amazon SageMaker, AWS, Python
  • Data Scientist

    2019 - PRESENT
    Self-employed
    • Consulted about the application of machine learning in concrete use cases (pharmaceutical industry).
    • Implemented and diagnosed machine learning models with frequent presentations of results to the client.
    • Automated the analysis pipeline in a medical study.
    • Scraped a specific website containing lots of data in HTML format and built a database based on this data.
    • Developed an Android application to organize courses and track and visualize evaluations for a specific business use case.
    • Built an automated system to evaluate the long-term performance of a machine learning model based on weekly new data.
    Technologies: Git, Python, RStudio
  • Data Scientist

    2019 - 2020
    Sopra Steria España
    • Developed new methods to measure business success for a retail client and its implementation in Python.
    • Performed a post-analysis of retail promotions using SQL and Python.
    • Optimized SQL queries to extract insights of large tables.
    • Restructured and optimized an internal Python package to extract and visualize statistics of large database tables.
    • Automated the analysis pipeline and also built a Python package that regularly produces a report based on data in a database.
    Technologies: Microsoft Excel, Azure, Databricks, Python, SQL
  • Data Scientist (Master Thesis Student)

    2019 - 2019
    Allianz
    • Wrote my thesis about machine learning methods to model life tables.
    • Performed preprocessing, analysis, and modeling of data with a size >100GB.
    • Built and tested an R package for the internal usage in the actuarial department.
    • Made my final presentation in front of experts as part of the official training series.
    • Implemented exhaustive performance optimization of R code using vectorization, parallelization, and optimized packages.
    Technologies: Plotly, Markdown, LaTeX, SQL, Python, R
  • Data Scientist

    2018 - 2019
    Allianz
    • Implemented and supported extensive interactive data-driven dashboards in R-Shiny.
    • Developed a product recommendation system for corporate clients based on the clients' characteristics and product history.
    • Built a productive automated system for the early detection of problems with products or business processes based on client complaint data.
    • Implemented the visualization of complex data and presentation of insights using Plotly, D3.js, and R Markdown.
    • Performed topic modeling and text mining of client complaint texts using LDA.
    • Made presentations concerning theory and programming packages within the field of machine learning.
    • Created internal programming packages to streamline and simplify frequently used data science tasks.
    Technologies: Microsoft Excel, Plotly, RStudio Shiny, SQL, Git, Python, RStudio
  • Researcher

    2017 - 2018
    Fraunhofer Institute for Industrial Mathematics ITWM
    • Worked on the project SENRISK (Senrisk.eu/) which predicted price fluctuations of corporate and sovereign bonds based on news sentiments.
    • Built recurrent neural networks in PyTorch to predict financial time series.
    • Developed statistical methods for fraud detection in the health insurance industry.
    • Implemented a Python package for financial time series prediction including an integration to a web service.
    • Constructed a software prototype in R Shiny to visualize the impact of different sample sizes in the context of fraud detection.
    Technologies: RStudio Shiny, PyTorch, Spyder, Anaconda, Linux, SQL, Python, RStudio
  • Intern

    2016 - 2017
    Universidad Técnica Federico Santa María
    • Implemented a type of software in C# to evaluate financial options based on the Black Scholes model.
    • Elaborated about a detailed report about the theoretical foundations of option price valuation.
    Technologies: Microsoft Excel, R, C#

Experience

  • EU Project SENRISK (Development)
    http://senrisk.eu/

    As a member of the Fraunhofer ITWM research institute, I participated in the EU-funded SENSIRK project. The main goal of this project was to predict corporate and sovereign bond prices based on news sentiments.

    My part was mainly the implementation of the prediction system. We used recurrent neural networks and boosting methods and built a Python package to streamline the whole process.

  • Analysis and Visualization of WhatAapp Chats (Other amazing things)
    https://github.com/l47y/whatsappalytics

    This is a Python toolkit to visualize WhatsApp chats. It offers some fun visualizations of single or group chats. Additionally, it has an interactive dashboard that can be used to navigate through visualizations. It transforms the original text file into a handy data frame and also handles different input formats (different IOS and Android versions).

  • Machine Learning Demonstration Tool (Development)
    https://github.com/l47y/ml_tool

    This shiny app serves as a little user interface to demonstrate some standard tasks of machine learning. You can upload an example data set and edit, visualize, and model it.

  • Android App Course Analyzer (Development)
    https://github.com/l47y/SiCourses

    This is an Android application to track given courses. It is used by a small group of persons for a specific business use case. You can insert a course and specify received evaluations.

    On the main page, you have an overview of all courses and you can export/import a list of courses. Finally, you can see statistics of the evaluations and a map shows the places where the courses have taken place with some additional information about it. Currently, it is only available in Spanish.

Skills

  • Languages

    Python, R, SQL, C#, Markdown, Kotlin, HTML, CSS
  • Frameworks

    RStudio Shiny, LightGBM, Selenium
  • Libraries/APIs

    Pandas, Ggplot2, XGBoost, Keras, Sklearn, Beautiful Soup, NumPy, PySpark, PyTorch
  • Tools

    Plotly, Amazon SageMaker, AWS Athena, Git, LaTeX, Sublime Text, Spyder, Microsoft Excel, AWS QuickSight, PyCharm, Microsoft PowerPoint
  • Paradigms

    Data Science, Business Intelligence (BI), Automation
  • Platforms

    RStudio, Amazon Web Services (AWS), Linux, Azure, Jupyter Notebook, Anaconda, Databricks
  • Other

    Data Analysis, Dashboards, Data Analytics, Mathematics, Dashboard Development, Data Visualization, Machine Learning, Random Forests, Dashboard Design, Reporting, Data Reporting, AWS, Financial Markets, Algorithms, Process Automation, Optimization, Web Scraping, Web Crawlers, Time Series Analysis, Statistical Analysis, Neural Networks, Android Development, Natural Language Processing (NLP)
  • Storage

    Databases, SQL Server Management Studio, MongoDB

Education

  • Master of Science degree in Financial and Actuarial Mathematics
    2016 - 2019
    Technical University Kaiserslautern - Kaiserslautern, Germany
  • Spent an exchange year in Financial Mathematics
    2016 - 2016
    Universidad Técnica Federico Santa María - Valparaíso, Chile
  • Bachelor of Science degree in Mathematics
    2013 - 2016
    Technical University Kaiserslautern - Kaiserslautern, Germany

Certifications

  • Big Data Fundamentals with PySpark
    OCTOBER 2019 - PRESENT
    DataCamp
  • Applying SQL to Real-world Problems
    OCTOBER 2019 - PRESENT
    DataCamp

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