Carl Mattsson

After moving abroad, I started my own firm. I have been working the vast majority of my time with a major non-life insurance company based in Finland. I have performed tasks related data engineering, data science, data architecture and machine learning engineering roles. I have also held the role of agile master. • Planned and implemented batch, micro-batch and streaming data architectures in the cloud (AWS, Azure, Databricks) for both structured and unstructured data. • Productized multiple machine learning models (e.g., XGBoost, LightGBM, TensorFlow, Open AI) developed by data scientists. • Developed MLOps, DataOps and DevOps libraries with Python. • Deployed and managed cloud infrastructure in AWS, Azure and Databricks. • Optimized data pipeline and API performance, significantly reducing operational costs for the client. • Developed and productized a customer retention model for corporate non-life insurance customers, helping account managers prioritize their work. • Technology stack: Python, TypeScript, SQL, Shell, Git, PySpark (Databricks, AWS Glue, AWS EMR), Apache Airflow, DataHub, relational databases, Delta Lake, Apache Kafka, REST API, infrastructure-as-code (AWS CDK, Databricks DAB), CI/CD (AWS CodeSuite, Azure DevOps Pipelines, Jenkins), Great Expectations, MLflow, automatic documentation generation (Sphinx), Power BI, Open AI.

I worked as a consultant and held such titles as Data Engineer and Data Scientist. • Developed and productized an application for determining optimal solar panel system sizes for housing cooperatives, helping drive sales. • Developed a real-time equipment monitoring system for predicting the service needs of elevators to enable predictive maintenance of the equipment. • Developed statistical models for predicting electricity and district heating production to help the client better meet the energy demands. • Created dashboards and built the underlying data pipelines for various use cases. • Deployed and managed cloud infrastructure in AWS and Azure. • Technology stack: Python, TypeScript, Scala, SQL, R, Shell, Git, PySpark (AWS Glue), AWS, Azure, IBM Cloud, CI/CD (Azure DevOps, Jenkins), containerization, Tableau, Power BI.

I held the title of data scientist in the bank's credit risk team, while also performing data engineering and data analyst tasks. • Led the development and implementation of the bank's next-generation retail client portfolio probability of default model. • Developed and maintained ETL pipelines. • Produced actionable analytics for business development and compliance. • Technology stack: Python, SQL, R, Shell, Git, Snowflake, Apache Airflow, Microsoft SSIS.

I worked at Easy Km during my studies. • Performed cost-benefit analyses of servicing contracts for leasing vehicle fleet. • Assisted the management in determining which contracts to terminate and at what price to accept future contracts.