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- Tasks: Lead data analysis and governance for content and research, uncovering trends and insights.
- Company: Join Law Business Research, a leader in providing essential data and intelligence across various niches.
- Benefits: Enjoy perks like remote work options, wellness allowances, and generous parental leave.
- Why this job: Be part of a passionate team that transforms data into compelling stories and insights.
- Qualifications: Experience in media or information services, with strong data analysis and team management skills.
- Other info: Work from anywhere for two weeks and enjoy company socials and mentoring opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Law Business Research is looking for a Lead Editorial Data Analyst to join its content, editorial and research division in London or Manchester. Law Business Research provides must-have data and intelligence to our highly loyal audiences across a range of niches and verticals. As part of our ongoing investment into deepening and improving our offer to audiences, we are growing our team of data analysts focused on editorial and content generation, and are looking for an experienced, passionate and rigorous team lead to architect that expansion. If you have prior experience in the media or information services sector, are passionate about using the right data to feed content strategies, identify trends and tell stories, and inspiring others to do the same, this opportunity is for you.
In this role, you will create and maintain a robust data governance framework for our content and research data; identify, quality assure and utilise external data sources; blend internal and external data to support our content and research objectives; and collaborate with various editorial and research teams to uncover trends and tell compelling stories from our data assets.
Key Responsibilities- Develop and implement a comprehensive data governance framework for content and research data.
- Work with content and research teams to ensure internal data remains in compliance with data governance framework.
- Continually assess and improve data quality standards to ensure our audiences get the answers and the insight they need.
- Identify, assess, and quality-assure external data sources to ensure alignment with our governance framework.
- Collaborate with content and research teams to identify trends and create narratives from data insights.
- Evaluate existing data visualisation tools and practices and create and embed programme for improvement, including procuring and onboarding new tools as appropriate.
- Analyse complex datasets to uncover actionable insights for our audience.
- Ensure compliance with best practices in data governance.
- Lead data projects and guide team members in data analysis and governance practices.
- Build a high-performing team of data analysts, with a blended onshore, nearshore and offshore approach to support effective resourcing.
- Lead the upskilling of our content and research teams in data analysis, data-led storytelling and data visualisation.
- Support the programme to transform our content into data that can be mined for trends and insights by our content creation teams, and also drive the creation of new data analysis tools for our subscribers.
- Support the development of internal and client-facing products driven by improved access to, and interrogation of, our existing and potential data.
- Technical skills
- Data analysis and visualisation: proficiency in tools like Infogram, Tableau, and Power BI.
- Statistical analysis: strong understanding of statistical methods and their application in data analysis.
- Data management: experience with data cleaning, data warehousing, and data governance.
- Machine learning: knowledge of machine learning techniques and their implementation.
- Programming: fluency in programming languages such as Python, R, and SQL.
- Critical thinking: ability to objectively analyse and evaluate data to make informed decisions.
- Communication: strong verbal and written communication skills to convey complex data insights clearly.
- Problem-solving: innovative approaches to overcome data-related challenges.
- Teamwork and collaboration: Ability to work effectively with cross-functional teams.
- Adaptability: flexibility to handle multiple projects and changing priorities.
- Experience managing teams of analysts a must; experience managing blended onshore / offshore resource desirable.
- Experience in information services or media a must; experience with the legal sector desirable.
Our people are our most valuable asset, as such, we offer a wide range of benefits to help ensure that all are supported:
- Start of employment: Eye care. Employee Assistance Programme. A day off for your birthday.
- After 3 months employment: Pension (4% employer contribution and 4% employee contribution).
- After 4 months employment: Life assurance.
- After probation: Cycle to work scheme. Season ticket loan. £350 annual wellbeing allowance to contribute to gym memberships or fitness classes. Puregym access. Perks at work platform access.
- After 1 year service: Private healthcare.
- Additional Perks: Company socials. Access to Employee Affinity Networks. Mentoring scheme. Volunteering Day. Mortgage Advice. Work from anywhere (2 weeks). Generous parental leave.
Lead Editorial Data Analyst employer: Law Business Research
Contact Detail:
Law Business Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Editorial Data Analyst
✨Tip Number 1
Familiarise yourself with the latest data visualisation tools like Tableau and Power BI. Being able to demonstrate your proficiency in these tools during interviews can set you apart from other candidates.
✨Tip Number 2
Showcase your experience in managing teams, especially in a blended onshore/offshore environment. Highlight specific examples of how you've led projects or improved team performance to align with the role's requirements.
✨Tip Number 3
Prepare to discuss your approach to data governance and quality assurance. Be ready to share insights on how you've implemented frameworks in previous roles and the impact it had on content strategies.
✨Tip Number 4
Research the legal sector and its data needs. Understanding the nuances of this industry will help you articulate how your skills can directly benefit Law Business Research and their audience.
We think you need these skills to ace Lead Editorial Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analysis, team management, and the media or information services sector. Use specific examples that demonstrate your skills in data governance and storytelling.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data-driven content strategies. Mention how your previous experiences align with the responsibilities of the Lead Editorial Data Analyst role and how you can contribute to the company's goals.
Showcase Technical Skills: Clearly list your proficiency in data analysis and visualisation tools like Tableau and Power BI, as well as programming languages such as Python and SQL. Provide examples of how you've used these skills in past roles.
Highlight Soft Skills: Emphasise your critical thinking, communication, and problem-solving abilities. Use specific instances where you've successfully collaborated with cross-functional teams or led projects to showcase these skills.
How to prepare for a job interview at Law Business Research
✨Showcase Your Data Skills
Make sure to highlight your proficiency in data analysis and visualisation tools like Tableau and Power BI. Be prepared to discuss specific projects where you've successfully used these tools to derive insights or tell compelling stories from data.
✨Demonstrate Leadership Experience
Since the role requires managing a team of analysts, share examples of your leadership experience. Talk about how you've guided teams in data analysis and governance practices, and how you’ve fostered collaboration across different functions.
✨Prepare for Technical Questions
Expect questions on statistical methods, data management, and programming languages such as Python and SQL. Brush up on these topics and be ready to explain how you've applied them in previous roles.
✨Communicate Clearly
Strong communication skills are essential for this role. Practice explaining complex data insights in a clear and concise manner. You might be asked to present a data story, so think about how you can make it engaging and understandable for a non-technical audience.
