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Data scientist in Basel
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Cognitive
Data Science

Welcome to the page of Dr. Jana Jarecki, a behavioral data scientist working with medical, psychometric, and risk data.

Hi, I’m Jana Jarecki, Data Scientist & Cognitive Researcher — I analyze human behavior by combining statistics with machine learning.

I lead research projects, do analyses, and publish at the real world solutions AG in Zurich. I have worked for leading institutions like the global top-100 University of Basel, Europe’s top 25 Aarhus University, and the Max Planck Institute in Berlin. I have a Ph.D. in computational modeling of cognition and my background is a double degree in Behavioral Economics/Cognitive Psychology from Germany’s number one university, LMU Munich.

 I have a strong publication record in peer-reviewed journals and global conference presentations. I have generated data-based insights into behavior (health, diseases, investments, consumer products) and perception (categories, features, sensory-motor, risk) by integrating different types of data (laboratory data, test results, sensor ratings, hand movements, web contents) collected by institutions, experiments, online surveys, web applications, mobile sensors, or financial providers and citizen science.

Port-
folio

neurology covid-19 health RCT smartphone nutrition risk DTx digital marker behavior depression economics PRO psychiatry observational persistence decisions information architecture health literacy RWD lab methods Switzerland learning UX analysis tools online reproducibility
  • All
  • Machine Learning
  • Inferential statistic
  • Descriptive statistics
  • Simulation
  • Quantitative data
  • Qualitative Data
  • Real-world data
  • Data visualization
  • Data Analytics Tools
  • Cognitive modeling
  • Data Type
  • Data Science
  • Experience
  • Method
  • Publication
  • Topic
Cognitive modeling / Data Science / Data visualization / Descriptive statistics / Inferential statistic / Machine Learning / Quantitative data / Simulation

Peer-
Reviewed
Publica-
tions

Areas of
Expertise

Evidence Requirements

Which questions to ask? Which evidence is needed? Ways to integrate evidence from multiple sources.

ML and Statistical Modeling

Train and test models, predict outcomes, and simulate processes, check for biases.

Data Management

Data integration from servers, data bases, spreadsheets, or real-world evidence from e.g., the internet or social media.

Translation to Models

What do verbal questions mean as models? Which co-variates are necessary? Which analyses are needed?

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