Data Scientist
Role details
Job location
Tech stack
Job description
The Data Scientist will play a core role in the new Ending Homelessness Accelerator Programme (EHAP). You will generate insights, understand trends, test hypotheses, and inform policy design that will support London Boroughs in their efforts to make homelessness and rough sleeping rare, brief, and non-recurrent.
Working with partners across LOTI, London Councils, the Greater London Authority (GLA), London Housing Directors' Group, Boroughs and the Centre for Homelessness Impact, you will use your skills to make a real impact in people's lives.
Working alongside the Data Projects Manager, the Data Scientist will support the programme to answer critical questions about homelessness in London by:
- Using machine learning and advanced analytics to identify the causes of homelessness, helping boroughs intervene before a crisis occurs.
- Building engagement and understanding of homelessness and rough sleeping data across the boroughs.
- Developing the data collection and analysis capability of the programme and its partners.
- Translating complex statistical models and their outputs into Data Stories and interactive dashboards that Housing Directors can use to inform policy and commissioning decisions.
- Experimenting with innovative analytical methods to improve the efficiency and effectiveness of homelessness data analysis and sharing lessons learned.
Main Responsibilities
Analysis and Insight Generation
- Select and apply appropriate and innovative analytical techniques to data and synthesise findings, specifically focusing on homelessness and rough sleeping datasets, including the Rough Sleeping Insights Tool, Temporary Accommodation, Inter-Borough Accommodation Agreement and more.
- Work as part of a multidisciplinary team, taking responsibility for analysis undertaken in response to outcomes and requirements identified by the team.
- Develop basic forecasting and predictive models to anticipate trends in homelessness and rough sleeping, helping to inform proactive policy responses.
- Interpret and identify patterns in data for a range of audiences, helping them understand potential conclusions and opportunities, and suggesting next steps for policy and intervention.
- Experiment with innovative methods to conduct analysis and share lessons learned with analysts in partner organisations to improve the efficiency and effectiveness of homelessness data analysis.
- Proactively ensure that data collection and analysis is organisationally effective and duplication is minimised.
Data Handling, Quality and Visualisation
- Prepare and cleanse data with experience at data cleaning and preprocessing techniques such as removing duplicates, handling missing data, and data normalisation, ensuring its accuracy and fitness for purpose.
- Use data visualisation tools to create visuals from complex datasets, telling compelling stories that are relevant to policy goals and can be acted upon by stakeholders.
Collaboration and Communication
- Effectively communicate with technical and non-technical stakeholders, including tailoring communication to specific audiences.
- Proactively seek perspectives from non-analytical peers including subject matter experts and frontline workers to support projects and gain richer user insights.
- Manage the production of best practice guides for data analysis within the team.
- Proactively build relationships that enable effective cross organisation collaboration within the Pan-London team and with external partners.
- Work with the Data Projects Manager to identify user requirements and feed these into future feature and functionality development
- Actively seek out new and insightful ways to present and visualise statistical data related to homelessness and rough sleeping to boost user engagement and policy impact.
Read about the job activities in more detail in the Job Description and Person Specification document attached below., LOTI's work constantly evolves as we try new things, learn and adapt to meet the needs of our members. This job description is therefore not intended to be rigid and inflexible but should be regarded as providing guidelines within which the post-holder works. Other duties appropriate to the post may be assigned from time to time.
Hybrid working
The nature of LOTI's activities is such that a significant amount of work can be conducted remotely. We currently envisage that 1-2 days a week (usually a Monday plus one other) will be spent in London, but the timing and frequency will be discussed and agreed with the team based on the needs of our members and London Councils' policies.
London Councils is the collective of London local government, the 32 boroughs and the City of London Corporation. They come together through London Councils to work in collaboration to deliver their shared ambitions for London and Londoners.
Through lobbying, collaboration and partnership, we ensure the voice of the London boroughs are united, and heard at a local, regional and national level.
We also run a number of services on behalf of the boroughs including the Freedom Pass, Taxicard and Health Emergency Badge (HEB) and London Lorry Control Scheme (LLCS).
Read more about London Councils - London Councils
Our Recruitment Approach
The application process involves answering a small number of application questions aligned to the essential criteria for the role. All applications will be processed using a blind sifting method. This means that personal identifying details will be removed to ensure fair and unbiased shortlisting of applications.
The panel sees only the anonymised generated CV that Tribepad builds from the Education and Employment History sections of the application form. Uploading a personal CV is optional and only helps auto-populate these sections - it does not replace completing them. Please ensure these sections are fully completed. If they're left blank, key information won't appear in the anonymised pack and fair review becomes harder.
Your full details and original CV are not shared with the panel until after the shortlist is agreed and you are invited to interview.
Requirements
Do you have experience in Tableau?, * Ability to understand business and policy problems and to address them using data from multiple sources
- Experience using predictive, statistical, or other mathematical techniques including supervised and unsupervised machine learning (including the ability to determine the best technique to solve a particular problem).
- An excellent grasp of standard statistical techniques for data analysis and exploration, such as regression and cluster analysis, and as well as experience using these techniques to solve real-world problems in a work environment.
- Strong proficiency in applying statistical techniques and machine learning algorithms using a variety of software/codebases e.g. R, Python to build reproducible processes.
- Ability to identify and effectively communicate data stories using data visualisation techniques with a range of audiences
- Ability to quickly research and learn new programming/modelling tools and techniques
- Ability to extract, clean, link, enhance and model data sets in a variety of software packages in a timely, effective and clear way.
- Experience visualising data sets through modern tools such as R, Python, PowerBI, Tableau etc
- Experience/knowledge about infrastructure for big data and data science analysis
- Experience of taking ownership and responsibility for your work, prioritising and organising work effectively and to operate as part of a team.
- A postgraduate degree in a quantitative field strongly related to data science, i.e. one that involves applied mathematics/statistics and coding or equivalent professional experience.
- Care about achieving outcomes that support innovation and benefit London and its population.
- Enjoy problem-solving in new, complex and sometimes ambiguous environments where both creativity and pragmatism are required.
Desirable
- Expertise in and experience of working with Homelessness Data.
- Understanding of information governance principles and data protection legislation.
- Knowledge of modern data management practices, including the technologies used, platforms and services.
- Ability to think creatively about the use and meaning of data patterns and insights.
- Experience of delivering insights to senior stakeholders and helping them to understand them.
Benefits & conditions
Contract details: Fixed term contract (18 months). Full time. Monday to Friday. 9:00 am to 5 pm. Hybrid working, some mandatory office days required.
