At a Glance
- Tasks: Analyse and manage data to enhance healthcare connections and improve patient care.
- Company: Join Doctify, a global leader in healthcare innovation and trusted connections.
- Benefits: Enjoy 28 days leave, remote work options, and a supportive learning environment.
- Other info: Dynamic team culture with opportunities for career growth and development.
- Why this job: Make a real impact in healthcare while developing your technical skills.
- Qualifications: Degree in STEM and proficiency in Python and Excel required.
The predicted salary is between 30000 - 40000 £ per year.
We’re Doctify. Doctify is the global platform built by doctors for doctors, on a mission to build the largest, most trusted global network of validated healthcare providers and experts. We connect patients with the right doctors, and doctors with respected peers, to ensure better care worldwide. Through verified patient reviews and professional skill endorsements, Doctify creates unmatched credibility for providers and empowers patients to choose care with confidence. Founded in 2015 and backed by $30m+ in funding, Doctify operates across 7 countries. We are uniting the global healthcare community, one trusted connection at a time. We do things differently here at Doctify, we are boldly leading a digital revolution in healthcare and are confident in our mission.
About The Role: We’re looking for a technically strong Data Analyst to help build and maintain a world‑class database that powers Doctify’s growth. This is a hands‑on, technical role. Industry experience is not required, so recent graduates are welcome to apply, but we’re looking for someone with genuine technical depth who can work independently, bring their own ideas for automation, and raise the standard of the data we hold.
- Processing and formatting data into the Doctify database, creating a clean, efficient and actionable store of data.
- Designing and building new methods to automate profile enrichment at scale.
- Working with third‑party data suppliers to source, evaluate and improve our data.
- Rigorously checking the data we hold and acquire for inaccuracies and duplicates, ensuring records are complete, accurate, and genuinely helpful to patients.
- Defining and monitoring data‑quality standards, and proactively flagging issues before they reach the sales, marketing or patient‑facing teams.
About you:
- Education: A degree in a STEM discipline (e.g. Computer Science, Mathematics, Statistics, Engineering, Physical or Life Sciences). No prior industry experience is required, and recent graduates are encouraged to apply.
- Python: Strong working proficiency in Python for data analysis (Pandas), including writing your own scripts. This can be demonstrated through study, personal projects or work.
- Excel: Advanced Excel, including lookups (VLOOKUP/XLOOKUP), data manipulation across large datasets, and confidence joining, splitting and reshaping data.
- LLMs: Hands‑on experience using LLMs (ChatGPT, Gemini or similar) both through the interface and via API, including practical prompt construction.
What We Offer: At Doctify, we shape careers with purpose. Our benefits are designed to fuel your growth, flexibility, and wellbeing.
- 28 days annual leave (25 + 3 between Christmas and New Year), earning up to 30 days leave with tenure.
- 2 weeks of remote working annually (within 3‑hour time zone of HQ).
- Hybrid working model.
- Enhanced Parental Leave.
- Medicash health cash plan.
- Competitive, benchmarked compensation.
- 3‑month immersive onboarding experience.
- Ongoing learning through expert‑led sessions, leadership insights, and soft‑skill development.
- Clear internal mobility pathways to accelerate your career.
The uniquely Doctify experience:
- Daily team huddles to connect, share wins and spark ideas.
- Regional Lunch Clubs & team socials powered by our Fun Police.
- Quarterly Doctifier nominated Impact Awards.
- Employee referral bonus: £700 (or local equivalent) per hire.
Our Commitment to DEIB: Diversity, equity, inclusion and belonging aren’t just values. They’re at the core of what makes us Uniquely Doctify. These principles shape how we work, how we design our policies, and how we bring our mission to life. As a global team, we know that diverse perspectives drive innovation and lead to better outcomes for patients, providers and each other. We’re committed to creating a fair, inclusive environment where everyone is heard, respected and empowered to thrive. We want to ensure that everyone has an equitable and comfortable experience throughout our hiring process. If you require any adjustments, we’re happy to discuss how we can support you. You can contact us at hiring@doctify.com.
Data Health Analyst employer: Doctify Limited
At Doctify, we are not just building a platform; we are creating a community that empowers healthcare providers and patients alike. Our commitment to employee growth is evident through our comprehensive onboarding, ongoing learning opportunities, and clear pathways for career advancement. With a flexible hybrid working model, generous leave policies, and a vibrant team culture that celebrates diversity and innovation, Doctify is an exceptional place for those looking to make a meaningful impact in the healthcare sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Health Analyst
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Doctify Limited when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Doctify Limited.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like Doctify Limited.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Doctify Limited’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Data Health Analyst
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Doctify Limited, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Doctify Limited aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Doctify Limited
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
