Inspiring Career Journey: Vlad’s Story at GORS

My academic journey began with a Bachelor of Science in Security and Crime Science at University College London (UCL). This course provided a comprehensive blend of criminology, social research, mixed methods research, psychology, and coding, which included statistics and machine learning. Additionally, I opted for modules in web development and simulation. A key component of my degree involved a six-month work placement, where I served as a Research Intern in the Evaluation Unit at the Mayor’s Office for Policing and Crime.

Discovering Operational Research

It was only after I joined the Civil Service that I became aware of the Government Operational Research Service (GORS). Upon learning about Operational Research (OR), I realised that many aspects of my degree had inadvertently touched on OR principles, particularly in the context of evaluating crime prevention strategies.

Motivations for Joining GORS

A significant element of my academic background revolved around measuring outcomes following interventions. This focus naturally aligned with my desire to engage in projects that yield meaningful real-world impacts. With my analytical mindset and enjoyment of coding during my studies, I was eager to apply these skills practically. In hindsight, I can confidently say that OR was an ideal match for my interests and abilities.

Additionally, I was fortunate to have a mentor from the Ministry of Justice (MOJ), whom I met during my university years through a charity. Although he was not directly involved with GORS, his insights into working within the civil service and the MOJ were invaluable in shaping my understanding of the sector.

Current Role and Responsibilities

At present, I serve as an Associate Data Science Product Manager. My role encompasses overseeing product vision, ensuring ethical considerations are addressed, managing stakeholders, identifying risks, and maintaining documentation for Data Science projects within Probation Data Science. Currently, I am focused on initiatives involving Large Language Models. My technical background proves advantageous in comprehending the nuances of these models and effectively communicating complex concepts to non-technical audiences.

Prior to my current position in product management, I held the role of Senior Data Scientist within the MOJ. My previous projects included coding initiatives related to large-scale data linking across the criminal justice system, fines enforcement, estimating reconviction rates, extracting insights from employee data, and prototyping a labour market dashboard. Each project has contributed to my growth, enhancing not only my technical skills but also my interpersonal, organisational, and communication abilities.

Highlights of My Career

Two standout projects come to mind when reflecting on my career achievements.

The first is the launch of our Contact Log Semantic Search tool. Each year, probation staff generate millions of reports on offenders, known as contact logs. These reports are often unstructured and vary significantly in writing style, which can complicate the search process for staff needing to refer back to specific documents or transition their caseloads to new colleagues. The use of a search tool powered by a large language model allows us to analyse these logs and identify relevant information more efficiently. By improving access to critical data, we aim to enhance staff engagement with offenders, ultimately supporting better rehabilitation outcomes and public safety.

Enhancing Data Linkage Efforts

The second notable project involved advancing our person data linking capabilities across the criminal justice system. Administrative data in this sector is frequently chaotic, with individuals lacking a unified identification number or obtaining new IDs for each interaction. This complexity hampers accurate statistical estimates and the assessment of intervention impacts, particularly when individuals change names, addresses, or other identifiers.

Fortunately, our talented data linking team developed Splink, an open-source package that has garnered over 10 million downloads globally. My contribution involved enhancing an existing person linkage by integrating an additional data source, thus improving the accuracy of our data linkage efforts.

Guidance for Aspiring Applicants

For those considering a career with GORS, the primary requirement is that at least 50% of your degree should be numerate in nature. Beyond this, curiosity is the key attribute to cultivate. I always advise individuals interested in any role to reach out to professionals already in the field for advice or insights; this can often lead to valuable mentorship opportunities.

While specific coding languages or prior experience may not be critical, what truly matters is your analytical aptitude. GORS values the ability to think logically about appropriate analytical techniques and the factors that should be considered. Once you have conducted your research, the ability to present your findings clearly and concisely—whether verbally, in writing, or through visual means—is essential.

Ultimately, success in this field hinges on practice. With a combination of curiosity, discipline, and creativity, you can thrive. For instance, many university students often fret over a lack of internship experience. However, dedicating time to personal coding projects using open-source data can prove far more beneficial for skill development and CV enhancement than traditional internship applications.