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Position: Data Scientist - Applied Mathematician
, Southampton , Stockholm , Sweden United Kingdom
Duties: Conducting exploratory and standard analysis of time series, geo-referenced time series, images and maps, and geo-referenced survey data; Developing novel data analysis methods and algorithms, data metrics, statistical and mechanistic models; Anomaly detection and data cleaning; Data integration: combining multiple data sources in analyses (spatial data, survey data, mobile operator data); Assessing and quantifying data limitations and uncertainty of outputs; Protecting subjects’ privacy, including acting in accordance with GDPR
Requirements: A PhD in applied research in a quantitative discipline. Fields of expertise may include signal processing, time series analysis, data mining, pattern recognition, image processing; and areas of application could be any sector that uses time series; Strong ability to reason under uncertainty: combining quantitative analytical thinking with contextual knowledge and using critical thinking to extract and interpret information and insights from data; Demonstrable experience in the exploratory analysis of time series, collected outside of experimentally controlled environments; Experience with sparse and irregular time series; Experience with spatial data and/or geo-referenced data; Proficiency in, and at least two years’ experience of, Python and its data analysis libraries, such as Pandas, NumPy, sklearn and Bokeh/Matplotlib; Experience in writing well-documented, maintainable code
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