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Nicolas Patzlaff

@nicolaspatzlaff

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Data Scientist specializing in end-to-end pipelines, machine learning, and actionable analytics.

Germany

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What I'm looking for

I’m looking to apply data science and machine learning to build end-to-end, cloud-based pipelines and dashboards that turn complex datasets into decisions. I enjoy partnering with stakeholders and improving data infrastructure to help teams ship faster.

I’m a Data Scientist with a strong foundation in statistics, machine learning, and large-scale data processing, shaped by interdisciplinary training in neuroscience and quantitative methods. I enjoy translating complex data into actionable insights through statistical modeling, performant analytics, and close stakeholder collaboration.

In recent roles, I’ve built and extended cloud-first pipelines for high-volume datasets—cleaning tens of terabytes of fMRI data for ML, designing EEG processing workflows, and re-implementing cloud-based automated connectomics proofreading for internal usage. I’ve also delivered simulation-focused statistical work at LMU Munich, developing and optimizing R code to support research modeling and performance improvements.

I bring a hands-on, product-aware mindset from engineering and data science experiences in industry, including building a customer-facing analytics platform with bespoke metrics and running early analyses on fleet data to improve wheel choice and repair timing. From ETL to modeling and visualization (including Tableau refactors that ran components tens of times faster), I focus on building data infrastructure that scales and helps teams move faster.

Experience

Work history, roles, and key accomplishments

Research Assistant

LMU Munich Statistical Consulting Lab

Jul 2025 - Oct 2025 (3 months)

Developed, optimized, and extended R code for a simulation study of miners’ radioactive exposure, supporting statistical modeling and simulation design in a research setting.

R Simulation Statistical Modeling Performance Tuning Experimental Design

Associate Research Engineer

Eon Systems

May 2024 - Sep 2024 (4 months)

Built a high-throughput cloud pipeline to clean tens of terabytes of fMRI data for an ML model, and designed an EEG cleaning pipeline. Re-implemented and debugged a connectomics proofreading pipeline and investigated multi-modality datasets by scraping metadata and creating data demos.

Data Pipelines AWS Azure Pyspark FMRI Data Processing EEG Preprocessing Connectomics

AI Developer

Constructivity

Mar 2024 - May 2024 (2 months)

Partnered with the CEO to conceptualize and develop a customer-facing analytics platform with bespoke metrics, translating requirements into an analytics product.

Metric Design Requirements Analysis Dashboarding Prototyping

Working Student Data Science

Krone Fleet

Feb 2024 - May 2024 (3 months)

Performed early analysis on customer fleet data to optimize wheel choice and repair timing, and initiated and led a data cleaning campaign to enable further analyses. Built Spark/Azure-based data transformation and analysis workflows for big-data customer datasets.

Data Cleaning Apache Spark Microsoft Azure Exploratory Analysis Decision Optimization Insights

Working Student Data Science

BMW AG

Jan 2023 - Dec 2023 (11 months)

Applied supervised and unsupervised learning to customer fleet data to uncover new insights for product development in automated driving. Built end-to-end ETL and analysis threads using Spark, Palantir Foundry, and AWS, refactored a Tableau dashboard to run tens of times faster, and created an automated recurring data-gathering script.

ETL Apache Spark Palantir Foundry AWS Tableau Data Automation

Research Assistant - Neuroscience

University of Tübingen

Oct 2021 - Jan 2022 (3 months)

Simulated randomly connected neuronal networks, analyzed network dynamics, and connected simulation results to recordings of rodent neurons.

Neuronal Network Simulation Scientific Computing Statistical Analysis

Student Assistant

Graduate Training Centre of Neuroscience

Apr 2020 - Oct 2020 (6 months)

Supported transformation of lectures from analog to digital and advised on the usage of video conferencing systems for teaching delivery.

Video Conferencing Technical Troubleshooting Documentation

Education

Degrees, certifications, and relevant coursework

Ludwig-Maximilians-Universität (LMU Munich)

Bachelor of Science, Statistics and Data Science

2022 - 2025

Grade: 1.3/1.0

B.Sc. program in Statistics and Data Science, including a thesis titled "Statistical Modeling of Auctions" under Prof. Thomas Nagler. Final grade reported as 1.3/1.0.

Graduate Training Centre of Neuroscience (University of Tübingen)

Master of Science, Neural and Behavioural Sciences

2019 - 2021

Grade: 1.3/1.0

M.Sc. program in Neural and Behavioural Sciences, including a thesis titled "Impacts of Neuronal Connectivity Changes in Different Network States" under Prof. Anna Levina. Final grade reported as 1.3/1.0.

Ruprecht-Karls-Universität Heidelberg

Bachelor of Science, Biological Sciences

2015 - 2019

Grade: 1.8/1.0

B.Sc. program in Biological Sciences, including a thesis titled "Automatic Tracking and Analysis of Mitochondrial Dynamics in Astrocytes" under Dr. Amit Agarwal. Final grade reported as 1.8/1.0.