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- Tasks: Analyse datasets to modernise a national digital screening service and resolve data issues.
- Company: Join a forward-thinking organisation focused on data transformation in healthcare.
- Benefits: Fully remote work, competitive pay, and opportunities for professional growth.
- Why this job: Make a real difference in healthcare by improving data quality and insights.
- Qualifications: Experience with SQL, Power BI, and strong analytical skills required.
- Other info: Collaborative team environment with a focus on innovation and impact.
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 employer: Jefferson Frank
Contact Detail:
Jefferson Frank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Network like a pro! Reach out to your connections in the data field, attend virtual meetups, and engage with professionals on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that Data Analyst gig.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your analytical projects, especially those involving Power BI and SQL. We recommend sharing this on our website or your LinkedIn profile to grab the attention of potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data analysis scenarios. Think about how you would handle data quality issues or translate anomalies into business rules. We suggest practising with a friend or using mock interview platforms to boost your confidence.
✨Tip Number 4
Follow up after interviews! A quick thank-you email can go a long way in showing your enthusiasm for the role. We believe that keeping the lines of communication open can help you stand out from the crowd.
We think you need these skills to ace Data Analyst
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 that showcase your analytical prowess. We want to see how you can contribute to our data transformation programme!
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 your skills align with our needs. Don’t forget to mention your experience with Power BI and geospatial data – we love that stuff!
Showcase Your Communication Skills: Since strong communication is key for this role, make sure your application reflects that. Use clear language and structure in your CV and cover letter. We want to see how you can translate complex data issues into understandable terms for stakeholders.
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 – just a few clicks and you’re done!
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, completeness, and how to assess validity. Being able to discuss specific examples of how you've handled similar data challenges will impress your interviewers.
✨Showcase Your SQL Skills
Since strong SQL skills are essential for this role, be prepared to demonstrate your proficiency. Brush up on common SQL queries and be ready to explain how you've used SQL in past projects to validate and analyse data. If possible, bring examples of your work or even a small project to discuss.
✨Communicate Clearly and Collaboratively
This role requires strong communication skills, so practice articulating your thoughts clearly. Think about how you can convey complex data issues in simple terms. Be ready to discuss how you've collaborated with stakeholders in the past to resolve data anomalies and define business rules.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that test your problem-solving abilities. Prepare by thinking through potential data issues you might encounter in this role, such as duplicates or missing data. Outline your thought process on how you'd approach these problems and what steps you'd take to resolve them.