I am both a practitioner (both software and hardware-wise) and a theoretician. I am also results-driven, with a focus on high quality. For example, for my thesis, I have two published ISI-journal articles. This commitment to quality is also reflected in my teaching, where I have consistently received high scores on course evaluations across a wide range of courses I have taught. In addition, I am easy-going and supportive, always finding time to help my colleagues and friends with any problems they might have.

Career

I hold a Ph.D. in Computer Science from the Department of Computer Science at Blekinge Institute of Technology (BTH) in Sweden. I have over 15 years of experience in academia, both as a teacher and researcher.

Blekinge Institute of Technology (2006 – 2020)

At Blekinge Institute of Technology, I worked as a full-time Lecturer and program manager for the Safety and Security Technology undergraduate program for six years, before pursuing my Ph.D. During this time, I taught a vast number of courses at both the undergraduate and graduate levels, including Computer Networks (with CCNA and CCSP elements), Databases, and various Network Security courses.

I completed my Ph.D. in Computer Science at Blekinge Institute of Technology in January 2018. My Ph.D. studies involved both national and international collaborations. For instance, I spent my first Ph.D. year employed at UC Davis, where I worked with Professor Felix S. Wu to develop a crawler for public Facebook data and a searchable database (via a web interface). I also worked closely with Dr. Piotr Bródka at the Department of Computational Intelligence at Wroclaw University of Science and Technology in Poland on research related to information cascades in social graphs, which were created from my substantial dataset collected by the crawler. My research has garnered significant attention, and I was even interviewed by The New York Times about my research and the dataset collected from Facebook (NYT article).

Scandinavian Airline Systems AB (SAS) (2019 – 2020)

I worked in the Commercial Analytics team as a Data Scientist, generating actionable insights from large data sets to support decision-makers within the organization. All of my projects involved full-stack work, ranging from data orchestration and engineering (ingesting, preparing, and cleaning data in Azure Data Factory, Azure Data Lake, and Azure databases) to model development (including training, evaluation, and model fitting), and creating end-user reports (using Microsoft Power BI) or application integration via Azure Dataflow. Notable projects include:

• Regression Model for Sales Forecast and Revenue Baseline: Developed predictive models to forecast sales and revenue trends.
• Classification and Prediction of Delayed Flights: Built models to predict flight delays, improving operational efficiency.
• Association Rule Learning: Applied this technique to derive insights on ancillary sales, enhancing revenue generation strategies.

Consid AB (2020 – Present)

Currently, I work at Consid AB as a Data Scientist, focusing on delivering high-quality data-driven solutions and insights across a variety of industries. My work involves applying advanced data engineering techniques, machine learning models, and providing actionable insights to support decision-making processes in various domains.

Assignments at Consid AB

2020 — Data-Driven Analyst, E.ON

Role: Data-Driven Analyst
Time Period: August 2020 – June 2021
Scope: 100%
Techniques & Methods: Google Analytics, Google Tag Manager, Google BigQuery, Microsoft Azure, Azure Data Factory, Data Orchestration & Data Engineering, Python, SQL, Snowflake, Power BI, Google Data Studio

Description:
I supported the business with comprehensive data and analysis to enable data-driven decisions. My work included full-stack tasks, from data orchestration and engineering to the creation of insightful end-user reports. Key responsibilities and projects included:

• Data Orchestration & Engineering: Managed the entire data lifecycle, including ingestion, preparation, and structuring of data using Azure Data Factory, Azure Data Lake, and Azure databases. I implemented robust ETL pipelines to ensure seamless data flow and integration, enabling efficient data processing and storage in Snowflake. I focused on designing data models, optimizing transformations, and ensuring data quality.
• End-User Reporting: Developed interactive reports using Power BI and Google Data Studio, providing actionable insights to stakeholders and helping them make informed decisions. I focused on user-friendly interfaces for data exploration and trend identification.
• GDPR Compliance: Played a key role in implementing a GDPR banner on eon.se to ensure compliance with data protection regulations, managing user consent, and tracking interactions.
• User Flow Tracking: Utilized Google Tag Manager and Google Analytics to tag and track key user flows on eon.se, including “sign electricity contract” and “report power cut.” I set up tracking mechanisms to monitor user behavior, optimize user experience, and improve website performance.
• Data Integration with Snowflake: Implemented data flows from multiple sources to Snowflake using Azure Data Factory, ensuring accurate data integration for analysis.

Through these efforts, I helped enhance E.ON’s ability to leverage data for strategic insights, operational efficiency, and regulatory compliance.

2021 — BI Specialist, Boverket, Karlskrona

At Boverket, I contributed to business intelligence projects, providing strategic insights through data analysis and reporting. My role included working with various data sources to ensure accurate data pipelines and reporting mechanisms.

2022 – Present — Data Scientist | Data Engineer | Backend Developer, E.ON

Role: Data Scientist | Data Engineer | Backend Developer
Time Period: April 2022 – Present
Scope: 100%
Techniques & Methods: Microsoft Azure, Azure Data Factory, Data Orchestration & Data Engineering, Python, SQL, Snowflake, Power BI, Qlik Sense, FastAPI, Plotly Dash

Description:
In this role, I support the business with data and analysis to enable data-driven decision-making. The work involves full-stack tasks, from data orchestration/data engineering (ingestion, preparation, and structuring) in Azure Data Factory/Azure Data Lake/Azure databases/Snowflake, to end-user reports (built in Microsoft Power BI and Qlik Sense). Key projects include:

• Data Orchestration with Snowflake: Implemented data flows from various sources to Snowflake using Azure Data Factory. Designed and developed complex ETL pipelines to ensure efficient data ingestion, transformation, and loading. Managed scheduling, job monitoring, and data quality to ensure seamless data integration and availability.
• Complex SQL Views: Developed complex SQL views to track contract status and key business metrics, aggregating and transforming data from multiple sources to provide a unified view of critical business information.
• REST Backend Development: Took full responsibility for developing a REST backend written in Python using FastAPI. The backend was designed to handle data processing tasks, provide APIs for data access, and integrate with other systems. I implemented API endpoints, business logic, optimized security and performance, and deployed the backend as Azure Functions. Additionally, I set up CI/CD pipelines in Azure DevOps for automated deployment and testing.
• End-User Reporting: Created comprehensive end-user reports in Power BI and Qlik Sense, providing actionable insights and visualizations for stakeholders to support data-driven decision-making.