Fabian Steuer, Developer in Dublin, Ireland
Fabian is available for hire
Hire Fabian

Fabian Steuer

Verified Expert  in Engineering

Data Scientist and Developer

Location
Dublin, Ireland
Toptal Member Since
March 27, 2020

Fabian is a data scientist and analytics engineer with more than five years of experience using the Python data science stack. As a full-stack data scientist, Fabian is skilled in the whole data value chain—from the initial data analysis to building predictive models and deploying the solution on various cloud platforms.

Portfolio

MyWallSt
Amazon Web Services (AWS), Apache Airflow, Google BigQuery, SQL, Python, Go...
NurseFly
Amazon Web Services (AWS), Snowflake, Data Build Tool (dbt), Looker...
MyWallSt
Looker, Apache Airflow, Heroku, AWS Lambda, Google BigQuery, SQL, Django, Python

Experience

Availability

Part-time

Preferred Environment

Amazon Web Services (AWS), Google Cloud Platform (GCP), Python, Jupyter, Go, Looker, Data Build Tool (dbt)

The most amazing...

...thing I've built is the complete data infrastructure of several startups—including data warehouses, pipelines, BI dashboards, and full-stack data applications.

Work Experience

Head of Data and Product Manager

2020 - PRESENT
MyWallSt
  • Built and maintained a data stack based on Google BigQuery, Apache Airflow, Stitch, DBT, and Looker.
  • Ensured that the product and marketing teams are tracking the right data, metrics, and KPIs.
  • Product-managed the premium investment subscription service of the company.
Technologies: Amazon Web Services (AWS), Apache Airflow, Google BigQuery, SQL, Python, Go, Data Build Tool (dbt), Looker, Product Analytics, Marketing Attribution, Business Intelligence (BI), Product Management

Data Engineer

2020 - 2020
NurseFly
  • Built a serverless API for analytics data using AWS SAM, DynamoDB, Lambda, and API Gateway.
  • Created an event-driven data verification system to ensure the correctness of data pipelines.
  • Optimized a marketing attribution data model in Snowflake, dbt, and Looker.
Technologies: Amazon Web Services (AWS), Snowflake, Data Build Tool (dbt), Looker, Marketing Attribution, Data Quality

Data Scientist

2018 - 2020
MyWallSt
  • Built a data warehouse based on Google BigQuery, Apache Airflow, and Looker that serves as a single source of truth for business and usage data.
  • Created the back-end architecture in Python that delivers stock market data to mobile apps and web applications in near real-time.
  • Used Jupyter Notebooks to gain insights into the behavior of mobile app users and drive product innovation.
  • Developed an event stream visualization web application in Django and D3.js to enable less technical stakeholders to do user research.
  • Designed and ran A/B tests to evaluate the impact of product changes.
Technologies: Looker, Apache Airflow, Heroku, AWS Lambda, Google BigQuery, SQL, Django, Python

Data Scientist

2017 - 2018
DogBuddy
  • Established Apache Airflow as the main workflow scheduler and wrote data pipelines for it.
  • Migrated the company's data warehouse from PostgreSQL to Amazon Redshift.
  • Designed BI dashboards and visualizations in Looker.
  • Created an additive model for time-series forecasting to predict the future demand for customer support agents.
  • Built an optimizer to improve the scheduling of the shifts of multilingual customer support agents.
Technologies: Looker, Apache Airflow, Redshift, SQL, Python

Trainee in the Impact Assessment Unit

2016 - 2017
European Commission
  • Ensured the quality of impact assessments and evaluations of major commission initiatives.
  • Participated in training sessions concerning stakeholder consultation, impact evaluation, and cost-benefit analysis.
  • Organized monthly events as a spokesperson of the Secretariat-General trainees.
Technologies: Microsoft Excel, Microsoft PowerPoint, Microsoft Word

Guest Scientist

2014 - 2015
Max Planck Institute for Dynamics and Self-Organization
  • Conducted research on the dynamics of resource dispersion in interaction networks.
  • Wrote an agent-based simulation of the resource exchanges in an ant nest in Python.
  • Visualized the resulting interaction networks and analyzed how resource flow metrics varied with time and initial conditions.
Technologies: Matplotlib, NumPy, NetworkX, Python

Machine Learning for Public Policy Making

https://www.ibei.org/ibei_studentpaper46_162056.pdf
I authored a research paper where I explored how machine learning can help to solve prediction problems in the public realm, such as predicting the probability that individuals commit crimes or estimating poverty levels based on satellite imagery. In a case study, I successfully use natural language processing techniques and random forests to predict if a restaurant is likely to commit a hygiene violation.
2015 - 2018

Master's Degree in Public Policy

Central European University | Institut Barcelona d'Estudis Internacionals - Budapest, Hungary | Barcelona, Spain

2011 - 2015

Bachelor of Arts Degree in Philosophy and Physics

Georg-August Universität Göttingen - Göttingen, Germany

2011 - 2015

Bachelor of Science Degree in Physics

Georg-August Universität Göttingen - Göttingen, Germany

JULY 2020 - PRESENT

Business and Financial Modeling

Coursera

APRIL 2020 - PRESENT

Programming with Google Go

Coursera

NOVEMBER 2018 - PRESENT

Bayesian Statistics

Coursera

JUNE 2017 - PRESENT

Machine Learning

Coursera

Libraries/APIs

Pandas, Matplotlib, Scikit-learn, NumPy, NetworkX, D3.js

Tools

BigQuery, Jupyter, Apache Airflow, Looker, Git, Jira, Trello, Slack, Microsoft Word, Microsoft PowerPoint, Microsoft Excel

Languages

Python, SQL, Snowflake, Go, R

Paradigms

Data Science, Business Intelligence (BI)

Frameworks

Django

Platforms

Amazon Web Services (AWS), Google Cloud Platform (GCP), Heroku, Linux, MacOS, AWS Lambda

Storage

Redshift, PostgreSQL

Other

Software Development, Machine Learning, Data Analysis, A/B Testing, Data Build Tool (dbt), Data Warehouse Design, Data Engineering, Causal Inference, Data Warehousing, Data Visualization, Google BigQuery, Marketing Attribution, Data Quality, Business Modeling, Financial Modeling, Product Analytics, Product Management, Deep Learning

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.

1

Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring