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- Tasks: Analyse data to modernise screening pathways and resolve data issues.
- Company: Join a national digital screening service focused on data transformation.
- Benefits: Fully remote work, competitive pay, and opportunities for professional growth.
- Why this job: Make a real impact by improving healthcare data processes.
- Qualifications: Experience in data analysis, SQL, and Power BI required.
- Other info: Collaborative team environment with a focus on innovation.
The predicted salary is between 36000 - 60000 £ per year.
An experienced Data Analyst is required to support a data transformation programme within a national digital screening service. The role focuses on modernising an end‑to‑end screening pathway by analysing multiple existing datasets, identifying data issues, and helping define future target data structures.
Core focus of the role:
- Define and validate the meaning and structure of future datasets
- Quantify and assess data quality issues
- Translate data anomalies into clear business rules with stakeholders
Essential skills:
- Assess data completeness, validity, consistency, uniqueness, and interpret operational or clinical implications
- Contribute to defining entities, relationships, and minimum viable datasets
- Map legacy fields to target definitions, resolve ambiguous usage, and propose standardised terminology
- Analyse duplicates, conflicts, and missing data, documenting trade‑offs and resolution options
- Work with subject matter experts to agree handling of anomalies and confirm business meaning
- Produce clear outputs such as issue summaries, dashboards, reconciliation lists, and sign‑off materials (experience with Power BI required)
- Create clear analytical documentation covering methods, assumptions, rules, and limitations
- Strong SQL for analysis, validation, and checking engineering outputs
- Proven experience with geospatial data, spatial formats, coordinate systems, and spatial analysis
- Ability to interpret geographical context and derive regional or national‑level insights
- Experience using official public datasets, particularly ONS open data
Soft skills required:
- Strong communication and collaboration skills
- Team‑oriented approach and ability to build strong working relationships
- Enthusiastic, engaged, and proactive
- Comfortable working independently and handling ambiguity or change
Nice to have:
- Knowledge of screening pathways, operational reporting, or relevant KPIs
- Familiarity with data governance, data dictionaries, and controlled vocabularies
- Healthcare experience
Candidates must be eligible for UK Security Clearance due to access to sensitive data and live systems.
Data Analyst in London employer: Jefferson Frank
Contact Detail:
Jefferson Frank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, join relevant groups on LinkedIn, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those involving SQL and Power BI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data-related questions and scenarios. Think about how you would handle data quality issues or translate anomalies into business rules. Practising your responses will help you feel more confident when it’s showtime!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly shows your enthusiasm and commitment to joining our team.
We think you need these skills to ace Data Analyst in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Data Analyst role. Highlight your experience with data quality issues, SQL skills, and any relevant projects you've worked on. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data analysis and how you can contribute to our data transformation programme. Keep it concise but impactful – we love a good story!
Showcase Your Skills: Don’t forget to mention your experience with Power BI and geospatial data. If you’ve tackled data anomalies or worked with public datasets, let us know! We’re looking for those specific skills that will help us modernise our screening pathway.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Jefferson Frank
✨Know Your Data Inside Out
Before the interview, dive deep into the datasets mentioned in the job description. Familiarise yourself with data quality issues, and think about how you would approach defining future target data structures. This will show your potential employer that you’re not just familiar with data analysis but also understand the specific challenges they face.
✨Showcase Your SQL Skills
Since strong SQL skills are essential for this role, be prepared to discuss your experience with SQL in detail. Bring examples of how you've used SQL for analysis and validation in past projects. If possible, practice some SQL queries beforehand so you can demonstrate your proficiency during the interview.
✨Communicate Clearly and Collaboratively
This role requires strong communication and collaboration skills. Be ready to discuss how you've worked with stakeholders in the past to resolve data anomalies or define business rules. Use specific examples to illustrate your ability to build relationships and work as part of a team.
✨Prepare for Geospatial Data Questions
Given the emphasis on geospatial data in the job description, brush up on your knowledge of spatial formats and coordinate systems. Be prepared to discuss how you've interpreted geographical context in previous roles and how you can derive insights from regional or national-level data.
