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Data Analysts - CSSF GMEL Partnership

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Organization: INTEGRITY
Closing date: 29 Jan 2021

Project Background

The UK government funds over £1 billion in programming per year through the Conflict, Stability and Security Fund (CSSF). Operating in over 70 countries, CSSF is central to the UK government’s work overseas. CSSF has contracted Integrity Research and Consultancy, and our partner LTS-Niras, to support the development of a stronger, more agile and more sustainable ‘ecosystem’ for monitoring, evaluation, learning (MEL) and their application in decision-making. To achieve this we shall, among other things:

  • Support CSSF in putting in place effective MEL frameworks, processes and tools, including evidence synthesis, at Fund and portfolio levels; and sharing promising practice at programme level.
  • Support CSSF in developing and implementing a capability-building strategy for MEL;
  • Strengthen CSSF organisational learning processes and incentives and support CSSF systems for the commissioning and use of applied research; and
  • Enhance CSSF use of digital tools.

Our theory of change envisages a stronger MEL ecosystem as one which enables CSSF to more effectively and consistently: demonstrate credible contributions to HMG priorities; use credible evidence for decision making; communicate insights transparently; and learn from its own practice.

The CSSF Global Monitoring, Evaluation and Learning contract applies an innovative approach whereby we work with the JFU and the network to co-create a responsive and utilisation-focused MEL architecture. We do this by co-designing ideas for implementation using an agile approach through stages of prototyping, testing, learning and adaptation.

Scope of Work

We are seeking four Data Analysts to support a new data analytics pilot initiative to improve the CSSF’s use of data in decision making. The Data Analysts will be tasked by four Pilot Leads and work closely with the Data Analytics Lead to extract, scrape, analyse and visualise data for CSSF teams. Specific responsibilities include:

Extract, Transform, Load (ETL) (60%):

  • Extracting and scraping a variety of data from different sources, including social media, open source websites, CSSF datasets (excel, csv), geospatial, and text-based reports.
  • Cleaning messy data and user-unfriendly excel spreadsheets into tidy relational datasets and identifying data quality issues.

Data analysis and visualisation (30%):

  • Analyse the cleaned data and identify relevant trends or correlations where possible.
  • Produce interactive and reactive dashboard solutions that are relevant, accessible and useful to CSSF clients.
  • Provide brief slide decks explaining the methodology behind the analysis and dashboard development.

Project design and learning (10%):

  • Support the co-design of the pilot’s approach and methodology with Pilot team and potentially with the client.
  • Contribute to project monitoring, reflection and learning to improve approaches throughout and at the end of the pilot.

Your Experience and Expertise

We are looking for a candidate that brings a combination of data analytics/statistics skills as well as a passion for using data in the public policy and programmes field.

Essential experience/expertise includes**:**

  • BA/BSc level degree or professional qualification in statistics, data analytics, computer science, maths or other relevant academic field with a data analytics focus. Candidates with data science bootcamp or online qualifications (e.g MOOCs) will also be considered provided they can demonstrate a strong portfolio of work and have a bachelors degree.
  • Demonstrated examples of data visualisation work produced, such as an academic capstone project or relevant work experience.
  • Understanding of data visualisation best practice principles, and ability to produce a wide variety of different visualisations (maps, network graphs, Sankey diagrams etc).
  • Proven competency in one of the following to clean, analyse and visualise data: Microsoft power BI (preferred) or Tableau; R or Python data science libraries and packages.
  • Experience of working collaboratively within a team and to support others relating to project-tasks.
  • Experience of working in fast-paced and high-pressure environments with the ability to adapt to new information and reprioritise.

Preferred experience:

  • 2-3 years' work experience in a data-focused and project-based role.
  • Experience of working with public-sector clients and interacting with UK Government IT systems.

Languages:

  • Written and oral fluency in English, with the ability to write clear and compelling narrative.

Security Clearance

  • Eligibility for UK Government security clearance. This means having lived in the UK for two of the past five years, including a period of 12 months consecutive residency in the UK.

Our offer/Further details

Duration: This position is a two to three-month consultancy, with an approximate start date in November or early December, to be confirmed at interview. The estimated end date is mid-late February 2021.

Time commitment: Full-time availability (40 hours/5 days per week) is preferred, but candidates with 80% +/4 days per week availability will also be considered.

How to apply:

If you are interested in applying for this position, please complete the application form at www.integrityglobal.com/apply and attach a tailored CV, Cover Letter and any relevant portfolio work to share (e.g Links to Github account or data visualisation work produced) at the bottom of your application.

This is a rolling recruitment, we will review candidates on a rolling basis and the vacancy. We encourage early applications. Please be advised that only shortlisted applicants will be contacted.

Integrity is an equal opportunities employer. And positively encourages applications from suitably qualified and eligible candidates regardless of sex, race, disability, age, sexual orientation, gender reassignment, religion or belief, marital status, or pregnancy and maternity. We will respect your confidentiality and abide by UK data protection laws.


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