About US

Flowminder is a non-profit foundation that specialises in the analysis of anonymised mobile phone data, satellite imagery, and household survey data for humanitarian and international development purposes.

Our mission is to enable decision makers to access the data they need to transform the lives of vulnerable people, at scale. We are striving to create a world in which decisions that can improve the lives of vulnerable people are based on the most appropriate evidence. We partner with decision makers and key stakeholders in national and international data systems to produce high-quality data, strengthen capacity, develop new methods and tools, and leverage novel data sources to improve the lives of vulnerable populations.

Flowminder researchers pioneered the use of mobile operator data for humanitarian purposes and were the first to use mobile operator data to monitor population movements following a large-scale disaster and a major infectious disease outbreak (the Haiti earthquake and cholera outbreak, 2010). Also, Flowminder was the first to show that mobile operator data can predict the spatial spread of an infectious disease.

We work with governments in low and middle-income countries, UN agencies, The World Bank and other development banks. Our funding comes from Bill and Melinda Gates Foundation, the UK government, development banks, UN and intergovernmental agencies. 

We are looking for Data Scientists with varying levels of experience to join our team and contribute to the wide range of humanitarian and development projects we are delivering. While the current situation is likely to start with home-working, we are looking for candidates that will join one of our offices based in Stockholm (Sweden) or Southampton (UK).

The Role

Data scientist is a senior role that entails data analysis and code development, as well as project design and business development. 

As a data analyst (applied mathematician) you will develop and test new methodologies for processing, analysing and interpreting large spatio-temporal datasets for the development and humanitarian sectors. You will report on your findings and methodologies in a way that is adapted to various stakeholders (academics, donors, end users).

As a developer, you will write/formulate queries to extract data from large/medium-size databases in a memory-efficient manner and will ensure sensitive data remain secure at all times. You will also support the development team in productifying/industrialising the methods/algorithms you develop.

As a senior team member, you will engage with end-users to understand their needs and identify which insights will be most relevant, as well as with donors to support business development. 

Main tasks will include:

  • 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

Your code and SQL development tasks will include:

  • Describing your algorithms and methods in a structured language (SQL) where appropriate.
  • Creating actual SQL queries that mimic algorithms and methods.
  • Revisiting SQL queries to make them more appropriate to particular data structures and data models available on different products.
  • Revising SQL queries, that are intended to be run repeatedly or on large amounts of data, for speed and efficiency.
  • Assessing the impact a data model has on how SQL needs to be written (often in a deconstructed form) in order to comply with a particular product architecture.
  • Tailoring the process of running SQL queries (for example by running many smaller queries rather than one big query) to accommodate for either limited storage capabilities or processing power of target machines or to accommodate large data sets.
  • Suggesting good data deletion strategies.
  • Creating and documenting workflows of which the actual SQL may only be a part.
  • Articulating which part of workflows requires what sort of (automatic or human) resource.
  • Conforming to potentially restrictive architectures and interfaces by being creative with how those architectures and interfaces are used.  This would include working with, and retrieving data from, APIs.
  • Working on shared resources, managing your work so that it cannot prevent other operations from succeeding.
  • Understanding the limitations appropriate to a data-sensitive environment.

In addition, you will also be involved in project design and business development, where tasks may include:

  • Researching the needs of stakeholders and context
  • Engage with end-users and donors
  • Create analysis/research questions
  • Conceptualise projects, activities and advise on the level of effort required

Finally, you will also be responsible for reporting analytical findings:

  • Choose dissemination methods that are appropriate for users’ technical capacity
  • Ensure results and conclusions are communicated clearly and can be understood by a non-technical audience
  • Clearly communicate any limitations of the data
  • Oversee and review data visualisations and reports
  • Take into account ethical issues around how data will be used
  • Disseminate work via presentations, workshops, conferences
  • Reporting findings and progress on methods internally, to technical colleagues and non-technical staff

We seek talented and devoted data scientists/data analysts who look to apply their skills to support current humanitarian and development efforts, and seek to provide accessible and data-driven solutions to inform decision-making in LMICs. Our focus is to implement and operationalise the high-quality data products and solutions that we, and occasionally others, develop. The outputs of our work have the potential to be published in scientific journals. However, while we occasionally spend the necessary time to publish articles we do not do this systematically. Our focus is on operational, rather than academic impact.  

In addition to scientific work, experienced candidates will have the chance to lead small to medium-sized projects or act as project director for certain initiatives.

About You

Your motivation to work with us should stem from your interest in tackling the following problems:

  • How to improve information extraction from mobile phone usage data (CDRs)
  • How to identify and characterise the patterns of normal human mobility and detect abnormal changes
  • How to ensure data products are computed in an efficient, robust and timely manner
  • How to support the humanitarian and development sectors to make the most of mobile operator data

Essential criteria

  • 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, for example, humanitarian and development sectors, public health, medicine, computer vision, robotics,  theoretical ecology, econometrics, or physics.
  • 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
  • Proficiency in SQL
  • Experience in writing well-documented, maintainable code
  • Excellent written and verbal communication skills in English
  • A genuine desire to see the outputs of your work improve the lives of vulnerable populations. A genuine interest in, and willingness to further understand, the mission and operations of our organisation

Desirable criteria: 

  • Knowledge and experience in the analysis of spatial data and time series, human mobility data or flow data;  data integration, probability theory and combinatorial analysis
  • Previous experience in large-scale data mining or machine learning
  • Experience with a Big Data ecosystem - algorithms, tools and technologies
  • Experience with database management
  • Experience with data visualisation and mapping
  • Experience in applying quantitative methods to support governments and humanitarian actors decision making
  • Experience of working on applied problems in low and middle-income countries and/or having spent sustained periods of time in low and middle-income countries
  • Experience with geographic information systems (GIS)
  • Experience with data privacy and privacy-preserving strategies
  • Experience developing data-driven projects, fundraising and project management is valuable
  • The ability to work well independently and as part of a team

Other organisations may call this role Mobile Data Scientist, Mid-Level Data Scientist, Senior Data Scientist, Lead Data Scientist, Data Analyst, Insights Analyst, Statistician, Mobile Data Analyst or Project design Analyst. The role may correspond to post-doctoral research associate in academia or principal investigator for more experienced candidates. However, our focus is operational, rather than academic.

The Benefits

  • Salary of up to £57,900 per annum
  • 37.5 hours per week
  • Flexible working hours
  • Support projects to improve the lives of the world’s most vulnerable
  • The opportunity to gain knowledge in various fields (such as public health, emergency coordination, disaster management, public services management) directly from experts in many countries
  • The opportunity to work on and explore large-scale and near-real-time datasets reflecting human mobility
  • Some home working allowed (initially only home working in the UK as guided by public health recommendations)
  • Traveling is common for many data scientists and part of the role for project leaders in order to develop an understanding of the context and needs of stakeholders
  • Collaborate with a talented and passionate team

To Apply

Applicants should email careers+da0721@flowminder.org with the following (preferably in pdf format):

  • A brief expression of interest outlining why you are interested in being part of the work
  • CV(s) (2 pages) with details of relevant experience

Please note that due to the very high volume of applications we receive, we greatly regret that we are unable to send personalised acknowledgements or give feedback on applications. Only applications following the requested application format will be considered.

 

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