Career Profile
Forward-thinking and driven Data Analyst with a PhD in Psychology and a broad foundation across the analytics spectrum. Experienced in leading data-driven initiatives at the intersection of business and analytics. Skilled at transforming complex data into actionable insights, meaningful KPIs, and compelling narratives for diverse stakeholders. Passionate about building collaborative, high-performing teams and leveraging AI and advanced analytics to drive editorial excellence and strategic impact.
Experiences
- Fostered a data-driven culture by developing KPIs focused on editorial engagement and user loyalty to enhance business strategies
- Led two strategic initiatives: harmonizing editorial dashboards and transitioning to unified data models to reduce redundancy,and standardize KPIs
- Built data pipelines and dashboards for key business initiatives
- Developed an editorial AI bot for content performance inquiries
- Used Airflow and dbt to manage and customize data workflows for extraction, transformation, and loading
- Built real-time dashboards for visualizing important editorial KPI:s
- Applied forecasting models for predicting future traffic patterns
- Used SQL (BigQuery), and R/Python for data analysis in my everyday work
- Frequent presentations to stakeholders with varying backgrounds
- Responsible for the design and execution of several A/B-tests related to user behavior
- Statistical advisor for undergraduate students covering consultancies such as choice of analytical approach, execution of analyses, and interpretations of the results
- Analyzed large datasets, encompassing data preprocessing, and predictive modeling
- Frequent presentations to stakeholders with varying backgrounds
- Utilized a wide array of visualization techniques to validate the data and support interpretations
- Collaborated with Hypocampus AB, a Swedish startup specialized on e-learning, to draw conclusions about study behavior
- Routinely used R and Python for statistical analyses
- Built machine learning models for predicting future dropout rates on a web-based learning platform
- Taught an university-level course, covering the basic principles in research methodology and statistical analysis
- Supervision of one Ph.D student, five Master’s theses, and 10 research assistants
- Built regression and anova models for hypothesis testing related to human cognition
Projects
Prediction
- An analysis of what a house should cost in Umeå, with respect to relevant features
Data extraction
- A demonstration of how to use the pandas package in Python for feature extraction in online user behavior
Machine learning
- A walkthrough how to predict future dropout rates using some of the most well-established machine learning algorithms
Bayesian inference
- Examining the effects of cognitive training using Bayesian statistics in R