About

Job market status

I am currently on the job market. If you are reading this and want to employ me, remotely or in the greater Hamburg area, please get in contact. A link to my CV should appear on this site, or you can email me.

James as a Data Scientist

Background

My empirical prowess stems from my economics education. After the two-year Masters of Science in Economics program at the Universität Hamburg, I began a PhD at the Graduate School of Economics, Finance, and Management in Frankfurt. My first two years were coursework, including advanced econometrics, time series analysis, and Bayesian inference. My research focus was on heterogeneous agents and their labor market outcomes. I have also noticed that my general economics training has tuned me into considering unintended consequences, incentives, and marginal benefits in a way that is often unique and useful in a business context.

I also have professional experience with Statista as a researcher for the Editorial Research Intelligence Department. We researched and prepared domain-specific dossiers on topics from the effects of the George Floyd killing to the cost of European monarchies. Upon joining the team, my writing reduced the turnaround for the drafting phase by over half, with fewer revision requests from the editorial team.

English is my mother tongue, and my German is advanced (B2/C1, depending on the day). I also speak intermediate Spanish (B1) and basic French (A2).

Programming

My first love was MATLAB, mostly because the syntax is so friendly to those of us who love matrix algebra. I am now using Python most often, and along the was I have used R, Stata, SQL, Bash, a little C++, and others. My academic projects focused on computational methods, primarily Bayesian methods (Gibbs sampler, Metropolis-Hastings algorithm, Kalman filter, etc) and optimization methods (Bellman optimality, endogenous grid search, hill-climbing algorithms, etc).

Lately I have expanded into machine learning. Averse to a black box, I find myself driven to understand the inner workings of a model before using it. Much of this stems from a lingering need for control over both my models and their interpretations. I have had a few conversations, for example, about the importance of knowing the variance when using a logistic regression, even though that is not reported by scikit-learn. At some point I will explore this further with an experiment.

I am also actively exploring certifications in AWS, namely machine learning and cloud computing. It is more technical than statistical, but I am committed to understanding the processes needed for modern data infrastructure. Here, I am more tolerant of black boxes.

Seemingly Unrelated Work History

Before returning to academia for my masters, I lived and worked on four continents. Jobs included tourism, English teaching, managing a hostel, and nonprofit fundraising. While these were chosen more as a way to fuel my desire for international experience, I took each position seriously, delving deep into the topics offered. The entire process has also endowed me with a library of general knowledge, helping me to create cognitive connections and arrange new data into a broader context.

Through this, I have developed a range of skills which have benefited me in surprising ways. First and foremost, living so long in such different cultural contexts required flexibility and self-reliance. It also bolstered my capacity for quickly acclimating to a situation, rapidly learning the pertinent details to understand my new surroundings. Secondly, as these were all public-facing positions, they developed my communication skills in all contexts, from written to large presentations.

They also required teamwork, and I thrive in a collaborative environment. After my years as a trip leader in adventure situations, I am comfortable at any point in the hierarchy, including leadership roles. I also handle crises well, as few office tasks are more stressful than facilitating a whitewater rescue. Furthermore, such a reliance on my colleagues garnered my capacity for recognizing their various strengths and allocating tasks efficiently.

Other interests

I identify as a nerd and throw myself into topics as they catch me. This has included international relations, linguistics, history, ecology, composting (particularly vermicompost), and whitewater kayaking. By no means am I an expert in these, with the exception of whitewater, but I find it useful to keep myself entertained. It also fuels my creativity.