Karina Kangur
Data Analyst @Iopt
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WORK HISTORY
Data Analyst @Iopt
Glasgow City, GB
At iOpt, I’m part of a team using IoT technology and data to help social housing providers make informed decisions and improve living conditions for tenants. My role focuses on interpreting complex sensor and environmental data, delivering actionable insights, and supporting smarter, more sustainable property management.Key responsibilities:Data reporting & automation:Develop accurate monthly and ad-hoc client reports, and streamline reporting workflows through automation to reduce manual effort and improve data quality.Data visualisation:Create clear and accessible visualisations and analytical outputs (Power BI, Python), enabling both technical and non-technical stakeholders to understand and act on complex data.Collaboration:Work closely with cross-functional teams (hardware, software, account managers) and external partners, shaping how data is structured, validated, and used across the organisation.Strategic analysis:Analyse trends in environmental and energy data to identify high-risk properties, inform retrofit decisions, and support wider strategic initiatives.
EDUCATION
University of Aberdeen
Master of Arts (MA), 2.1, Psychology
University of Aberdeen
Master of Research (MRes) with Distinction, Psychology (funded by James S. McDonnell Foundation)
Pärnu Ühisgümnaasium
High School Diploma, Mathematics, Chemistry, and Physics
University of Aberdeen
Doctoral researcher (PhD), Psychophysics (funded by Biotechnology and Biological Sciences Research Council)
SKILLS
ABOUT KARINA KANGUR
Experienced data professional with 9+ years of experience working with data across IoT, government, tech, and academia. I specialise in statistical analysis, data pipeline design, and data storytelling. My focus is on communicating complex findings clearly, to the right audience, and with impact.I have a proven track record of delivering measurable outcomes. These include identifying high-risk social housing through IoT sensor data, uncovering socioeconomic predictors of workplace bullying and harassment, and helping clients save time and money through smart digital automation and scalable data solutions.I have worked closely with other analysts, developers, academics, and business teams to shape how data is structured, validated, and used across organisations. I aim to make data and complex datasets accessible and actionable. Whether supporting reporting improvements, helping drive better data quality, or mentoring others on analysis and interpretation, I aim to simplify data patterns into practical insights that can help other people.Core tech stack: Python, SQL, R, Databricks, Power BI, Tableau - but always keen to learn more.
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