LOTI Data Careers FAQs


Overview

Our first LOTI’s Data Careers Day was a celebration of the benefits of working in local government data roles. The online virtual showcase explored the importance of data roles in planning, strategy and delivering services that have a direct impact on our lives. 

As part of the session we explained the roles available, the potential career paths, training and development opportunities and provided insights into a day in the life of a data team member. 

The following FAQs is based on questions we received on the day:

FAQs

What’s the work life balance like in local government vs corporate?
Local government contracts tend to be 35 hours a week with good standards for annual leave and flexible working arrangements. In some teams working different and longer hours is required and in emergency response situations hours can be much longer. For example many data teams worked long hours during lockdowns to ensure track and trace and infections data being provided daily by Public Health England was processed quickly so that residents could be notified to isolate to help prevent the spread of infection.

What kind of technical skills are required to work as data analysts?
Proficiency in using query languages such as SQL, Hive, R is essential. Being able to extract, clean and model data is a requirement along with data matching. R and Python are the most commonly used languages and the required experience of these will depend on the seniority of the role. Having a good statistical and mathematical mindset is key to the analytical aspect of the job while applying these skills in project contexts will be the most desirable skills for those hiring.

Are there opportunities to work remotely or hybrid?
Yes! While each Council in London has their own policies most are currently working in a hybrid model. For some specific roles fully remote may also be possible.

Would you accept job applications from non-UK residents?
This is set by individual Councils in London but most look for staff to be based in the UK.

What kind of opportunities do you get for further learning?
Many boroughs offer apprenticeships which can be used to develop data analysis and data science skills such as machine learning. LOTI also works with boroughs to provide training and learning opportunities as part of the LOTI Data Science Network.

As a current university student, what topics / programming languages/ frameworks/ databases would you recommend looking into? E.g. Python, SQL
Python, R, SQL and data visualisation tools such as Power BI, Tableau and D3.

What differentiates the good data scientist from the great?
Communication skills and teamwork! Being able to convey your analysis and models to a range of non technical people is a challenging but important skill. As an analyst or data scientist you will need to be able to support non technical subject matter experts to understand how your work can help answer business or policy questions. Telling a story with your insight can sometimes involve picking just one element of a complex analysis to emphasise but this can be key in helping non technical audiences to understand your work and take action using it. 

Do you have part-time/summer/volunteering roles for people who want to get involved with LOTI but cannot commit to a full-time job right now?
Not right now but this is something we are looking into!

What sorts of datasets would a data analyst typically be able to access and work with?
Councils operate around 600 lines of business ranging from schools and social care through, environment and waste, elections, public health, high streets and local business support, council tax, housing, parking and many more. For each of these areas unique datasets are available from customer records to 3D planning models to historic measurements of air quality. Analysts will also typically access many open data sets such as those available via the London DataStore and demographic data published by the ONS. Those working on supporting High Streets following COVID have access to anonymised spend and mobility data.

How do you feel that the work you do in data roles impacts the communities you serve?
There are many examples where data work has had an important impact on communities. During COVID lockdowns, Councils in London used data matching techniques to identify and support vulnerable people shielding so they could be offered support with accessing food and medicine. Currently work on air quality is helping to shape policy around how roads are used near schools. 

What are the ethical implications of local government data science?
Community services directly affect the lives of local people, and given the close proximity of councils to the residents they serve, practitioners need to understand the ethical implications of their work as part of their professional skill set. LOTI are working on a set of resources to support councils further develop their ethical use of data. You can find our latest work on data ethics here 

Opportunities for Collaborative working between Council and sharing best practices.
LOTI supports Councils in London to collaborate and share best practice. The LOTI Data Science Network brings together analysts and data scientists to share technical challenges and successes and encourages the exchange of ideas and skills. Our Data Practitioners Networks discuss the key big picture challenges facing all those data roles and our Data Leaders Network covers strategic questions.  There are opportunities to come together to develop London wides data products such as the Digital Exclusion Map which was a collaboration between 5 boroughs LOTI and the GLA

How important are formal qualifications for data roles? I work in ICT in a council bordering London, all my data work is self taught as no budget for training
Formal qualifications are not a requirement. Skills and experience are what count. If you can demonstrate your capability in applying your technical skills in a project context you are suitable for a data role. One way you can build relevant applied skills is by getting involved in Citizen science projects. Contributors to platforms such as wikidata, openstreetmap and social media can expose you to local knowledge sharing and help to build relevant skills.

 

Data

Jay Saggar
1 April 2022 ·