Robin Opdam
Data Scientist at Metyis
Currently also working on:
- Learning about and working on generative AI applications.
- Started on Terraform basics.
About me
I am a Data Scientist with experience in bringing machine learning models to production. Over the years I have gained hands-on experience on
ML Engineering, Data Engineering, Generative AI, DevOps and the big 3 cloud platforms.
Always eager to learn within and outside of my field with a proactive and curious mindset.
This website showcases my projects, experience, education and contact information.
Tech Stack:
- Data Science: Python PySpark, SQL, NoSQL, R
- Machine Learning: Scikit-learn, Spark, MLlib, Tensorflow, MLFlow
- Data Engineering: Azure Data Factory, ELT/ETL pipelines, blob storage
- Product Management: Azure Boards, Jira, Confluence, Azure Wiki
- Experimentation Design: Hypothesis Testing, Power Analysis, Factorial Experiments
- DevOps: Azure, Gitlab, Github, GCP
- Database: BigQuery, NoSQL (CosmosDB)
- Visualisation: PowerBI, Plotly Dash, Shiny, Looker Studio
- App Deployment: Docker, GCP, Azure, Heroku (FASTAPI, OAUTH)
- CI/CD: Azure DevOps, Gitlab, Github
- IDE: VSCode, Databricks, Jupyter, RStudio
Projects
Contributions to Chainlit
Chainlit is an open-source async Python framework that makes it incredibly fast to build Chat GPT like applications with your own business logic and data.
More contributions to come!
Dec, 2023
Ergobot, the ergogenic chatbot
Definition: "An ergogenic aid is any substance or phenomenon that enhances performance".
Ergo-log collects studies on ergogenic aids, the Ergobot is a smart chatbot interface based on ChatGPT and a vector database of scraped Ergo-log articles.
The people at Ergo-log enjoy sporadically using Ergobot!
Aug, 2023
Deploy Containerized Plotly Dash App with CI/CD (P2: GCP)
Jan, 2023
A sequel to deploying a containerized Plotly Dash app (to GCP)
With Heroku moving to paid tiers I wanted to try Google Cloud Platform for deploying the same container. This is a sequel to deploy the same container from part 1 using a CI/CD pipeline to deploy a container to Google Cloud Run.
Jan, 2023
Student placement tool for yearly 'bedrijvendag' of JSVU
Every year the Juridische Studenten Vereniging te Utrecht (JSVU) organizes a 'bedrijvendag' where students and companies get introduced to eachother based on student preferences and study year.
Created an online tool where the students, their preferences and the available companies and introduction rounds can be uploaded. The tool instantly produces a student matching that can be downloaded as an excel file.
Used OOP in Python, Docker, Github Actions, Dash, and Heroku to have the online tool always available and deploy any future changes through CI/CD
Jan-Mar, 2022
Deploy Containerized Plotly Dash App with CI/CD (P1: Heroku)
June, 2021
A guide on deploying a containerized Plotly Dash app
Step-by-step guide on how to use Github Actions to build a CI/CD pipeline and deploy a containerized Plotly Dash app to Heroku.
- Towards Data Science article
- App is now deployed on GCP (see P2 above)
- Code Repository
June, 2021
Focus
March, 2021
An article on how to tap into your focus and keep it
A brief summary of things I picked up on how to focus, hope it enables others to focus as well!
March, 2021
Master Thesis: Comparison of Deep Learning Product Recommendation Engines in Different Settings
This work sheds a different light on the differences between deep learning and classical recommendation algorithms by comparing them on both a Movie dataset and a Fashion dataset. Their performance is thoroughly compared based on their implementation and the resulting Recall@n and NDCG@n scores.
Feb-Aug, 2020
Portfolio Website
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You are here
Ongoing
Created this portfolio website using HTML, CSS and JavaScript
Launched in November 2020
Ongoing
Associate Big Data & Analytics
From Jul 2022
Metyis: Associate Big Data & Analytics
Working on right now!
From Jul 2022
Analyst Big Data & Analytics
Nov 2020-Jul 2022
Metyis: Analyst Big Data & Analytics
Working with different clients, technologies and teams to bring impact.
Next to data science projects I worked on data engineering, ML engineering and data visualization
Nov 2020-Jul 2022
Graduate Intern Data Science
Feb-Aug, 2020
Metyis: Graduate Intern Data Science
Applied business rules to improve recommendations on the website of one of its clients using Python
Built a dashboard combining different marketing channels with Funnel.io for campaign tracking using Google Data Studio
Wrote my MSc. thesis about a Comparison of Deep Learning Product Recommendation Engines in Different Settings (9/10)
Feb-Aug, 2020
Intern Data Analyst
Aug, 2018
Schiphol: Intern Data Analyst
Analysed passenger security data to provide insights in staffing for different security filters. Introduced a new measure which combined several known features to measure under- and overstaffing of the security lanes.
Used Python and R for Exploratory Data Analysis
Created an R Shiny tool to view the trend of this new measurement in parallel with for example, throughput time.
Aug, 2018
MSc. Business Analytics
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Magna Cum Laude
Courses include: Advanced Machine Learning, Reinforcement Learning, Data Mining Techniques, Information Retrieval and Statistical Models.
2018-2020
VU: BSc. Business Analytics
The objective of this two year master programme is to enrich our understanding of the applications of Data Science and Optimisation to in-company problems. The programme offers a broad selection of courses in which I focused on machine learning
With great interest in the subjects I finished the programme with an average of 8.5/10 and a 9/10 for my thesis.
2018-2020
Exchange Programme
Courses include: Operations Management, Quantatative Risk Analysis, Strategy
2017
SMU: Exchange Programme
Living and studying abroad have brought me many things including: international relationships, different cultural views, proficiency in the english language.
Important is that it has showed me the possibilities of one's future are endless if you are willing to put in the work.
2017
BSc. Business Analytics
Courses include: Advanced Programming, Stochastic Modeling, Statistical Data Analysis, Machine Learning.
2015-2018
VU: BSc. Business Analytics
A combination of Computer Science, Mathemathics and Business management focussed on the transformation and handling of big data. The programme is based on practical assignments that provide hands on experience with dissecting problems, analysing and optimisation.
Finalised the programme with a project analysing bottlenecks within Schiphol Security lanes data using Python and R, Grade: 8/10
2015-2018
Happy to connect!
robinopdam@hotmail.com