Lead data analyst – Strategic Insight Unit

It’s the Met’s job to keep Londoners safe. That isn’t just down to front-line policing. We need specialists like you to improve what we do and how we do it. Our Strategic Insight Unit (SIU) combines advanced data analytics, behavioural science and social research skills with expertise in operational policing to deliver valuable empirical insight to the Met.

Join us, and you’ll make a make a big difference to our decision making.

The team

We are looking for a lead analyst to join our Strategic Insight Unit, a multi-disciplinary analytical team at the heart of the Met. We combine advanced data analytics, social research and behavioural science with expertise in operational policing and an understanding of the Met’s strategic landscape.

The SIU delivers empirical insights in support of evidence-based policing via three main routes:

• We explain: we use behavioural science, data analytics, operational insight, and social research to understand what's happening, how and why

• We innovate: we bring fresh thinking and new ideas into the Met to challenge the status quo and change Met policies and practice

• We test: We work with operational Met units and external experts to co-design and deliver scientifically robust trials and evaluations

The role

As a lead analyst in the SIU you will support the Met’s principal criminologist, Head of the SIU and your analytics team to deliver research projects. You will do this by constructing analysis-compatible datasets, automating and improving existing data practices and employing various data science techniques to produce high quality robust analysis that informs MPS decision making and practices. You will be able to translate the results of your analysis into meaningful insights that help front-line officers and senior leaders make strategic decisions on how to deal with the complex challenges facing the Met.

You will be responsible for managing projects from inception to the production of finalised outputs, which will involve managing resources and the sometimes conflicting demands of stakeholders, as well as conducting the various administrative functions of project management. In addition, you will be responsible for managing and supporting junior analysts.

Essential criteria and responsibilities:

Qualifications and experience

• you need hold a minimum of a degree-level qualification, preferably a masters, in a quantitative subject such as statistics, economics, computer science or a relevant field with a substantial component of quantitative analysis
• you will have a minimum of two years relevant work experience or equivalent academic experience

Data manipulation

You will possess advanced data wrangling skills and be able to demonstrate proficient use of structured query language (SQL) and R or Python in the following areas:

• dataset building: constructing analysis compatible datasets from multiple sources, and across different platforms, in a timely manner. This will involve joining datasets together. For example, by writing nested sub-queries in SQL and matching on common IDs before reading the data into R/Python for further wrangling, as well as liaising with data owners in different teams to request appropriate bespoke cuts of data
• data cleaning: appropriately handling missing values, including basic imputing, and reformatting data, for example recoding, creating new variables, changing the shape of datasets. You will have a good understanding of the quality and limitations of the data.
• automation of data processing: be able to write efficient scripts that facilitate many of the functions of a data analyst, including reading and processing data and automating processes for repeated tasks, for example writing functions, for-loops and procedures
• you will write clear code that follows standard conventions to allow for seamless quantitative analysis
• you will proactively identify opportunities for improving existing data practices, for example, by identifying opportunities to automate data processing, improve efficiency and employ new analytical techniques

Data analysis

• data visualisation: have an excellent sense for what visualisations best convey information pertaining to the research question at hand and be able to produce high quality graphs, charts, rudimentary heat maps and other descriptive statistics
• data analysis: in addition to producing descriptive statistics, be able to conduct basic statistical tests, implement key data science techniques and run simple machine learning models, such as regression-based models, classification methods in R or Python

Project management

• manage projects from identification and scoping to the production of finalised outputs. This will involve conducting the administrative functions of project management, including:
  • noting actions
  • prioritising tasks and resources
  • reconciling conflicting demands
  • chairing meetings
  • working to deadlines
  • ensuring adherence to governance processes
• be able to translate the analytical needs of stakeholders into concrete research questions with accompanying feasible research plans that make appropriate use of SIU resources and are proportionate to business needs. You will understand the benefits and limitations of different evaluation methodologies and be able to set stakeholder expectations accordingly

Report writing and presentation

• be able to translate the results of your analysis into meaningful insights for non-technical audiences including senior leaders and external stakeholders, both verbally and in writing, to inform board-level decision making
• be able to produce high quality research outputs, such as reports and presentations, which summarise findings in a succinct and appropriate way for your audience

Communication and leadership

• ensure you build effective working relationships with your direct report. Supporting the progress of projects, setting objectives in alignment with SIU priorities, as well as facilitating their professional development and well-being
• be proactive in maintaining an open line of dialogue with your line manager, updating them on project progress and understanding when it is necessary to seek their input
• work pro-actively and flexibly with colleagues across the Met to support organisational needs and stakeholder requirements
• be responsible for reviewing the code, analysis and research outputs of more junior analysts and providing quality assurance
• be expected to promote a trustworthy, fair and understanding work environment, by demonstrating organisational values and behaviours

Desirable Skills

• some knowledge of applied statistics, including:
  • fundamental probability concepts and distributions
  • hypothesis testing
  • model robustness checks
  • the fundamentals of regression modelling and classification
  • a general good sense for what statistical techniques are appropriate for a given research question and dataset
• knowledge of geo-spatial analytical techniques
• familiarity with empirical research methods, including experimental and quasi-experimental methodologies is also favourable

Additional Information

If you are successful at the initial application stage, you will be asked to complete a data analysis task prior to interview.

There’s a great deal to look forward to in return. As well as opportunities to grow and learn, you’ll enjoy benefits including substantial annual leave, a Civil Service pension with an average employer contribution of 27%, interest free season ticket loans, flexible working conditions and more.