Policy Analyst

Uxbridge
1 week ago
Create job alert

Are you a strategic thinker with a passion for shaping policy to improve communities? Join our team as a Policy Analyst and help develop and evaluate policies that will make a tangible impact on the housing and planning landscape in London.

Key Responsibilities:

  • Policy Development: Research, analyse, and support the creation of new housing policies, strategies, and initiatives. Work closely with senior leadership to align policies with the council’s objectives and local needs.

  • Policy Evaluation: Monitor and evaluate the effectiveness of existing policies. Use data and evidence to assess outcomes, identify areas for improvement, and make recommendations for policy updates.

  • Research & Data Analysis: Conduct detailed research on housing trends, legislation, local needs, and best practices. Analyse quantitative and qualitative data to inform policy decisions.

  • Consultation & Stakeholder Engagement: Engage with stakeholders including local communities, housing associations, developers, and government agencies. Organise and participate in consultations and focus groups to gather feedback and inform policy development.

  • Report Writing: Prepare comprehensive reports, policy briefs, and presentations for senior management, elected officials, and external stakeholders. Communicate complex policy analysis clearly and effectively.

  • Legislative Monitoring: Keep up-to-date with national and regional housing policies, legislation, and best practices. Assess the potential impact of legislative changes on the council’s policies and operations.

  • Cross-functional Collaboration: Work closely with planning officers, housing development teams, and other departments to ensure alignment between policies, strategies, and operational activities.

  • Public Engagement: Contribute to public consultations and policy discussions, ensuring that community input is included in policy development. Present policy proposals at council meetings, public forums, and workshops.

  • Performance Measurement: Develop and implement mechanisms to track the success of housing and planning policies, including the creation of key performance indicators (KPIs).

    Essential Qualifications & Skills:

  • Experience: At least 2-3 years of experience in policy analysis, research, or a related field, preferably within local government or a housing/urban planning organisation.

  • Knowledge: Strong understanding of housing policies, urban development, planning legislation, and social policy issues. Familiarity with UK housing law and local government procedures is essential.

  • Research & Analytical Skills: Proven ability to conduct qualitative and quantitative research, analyse complex data, and draw actionable insights for policy development.

  • Communication Skills: Excellent written and verbal communication skills, with the ability to present policy recommendations to a variety of audiences, including senior management, councillors, and the public.

  • Project Management: Ability to manage multiple projects simultaneously, ensuring deadlines are met and resources are used effectively.

  • Stakeholder Engagement: Experience engaging with diverse stakeholders, including government bodies, developers, housing providers, and community groups.

  • IT Proficiency: Proficient in Microsoft Office and data analysis tools (e.g., Excel, SPSS, or similar). Experience with GIS mapping tools or housing management systems is a plus.

  • Attention to Detail: High attention to detail and ability to critically assess and synthesize information from various sources.

    Desirable:

  • Relevant Qualifications: A degree in Public Policy, Housing, Urban Planning, Social Sciences, or a related field. Postgraduate qualifications or training in policy analysis is a plus.

  • Experience in Housing or Urban Planning: Experience working within the housing sector, urban planning, or local government policy development.

  • Multilingual: Ability to speak additional languages is a plus.

    What We Offer:

  • Competitive salary and a comprehensive benefits package.

  • Opportunities for professional development and career progression.

  • A collaborative and inclusive work environment.

  • Flexible working arrangements and a focus on work-life balance.

  • The chance to make a meaningful impact on housing policy and urban planning in London

Related Jobs

View all jobs

Business Intelligence Analyst

Operations Analyst

Operational Analyst Consultant

Commercial Data Analyst

Data Analyst (Financial Market Data)

Operational Analyst Consultant

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.