Job Description

Please note:

This role works from our Farringdon (London) office 3 days a week. If you can not accommodate this, we unfortunately can't consider you for the position. We can not offer sponsorship for this role either, so if you don't have right to work in the UK, please refrain from applying.

About Skin Analytics

Skin Analytics is an award-winning, health tech company that works with dermatology teams to deploy world-leading skin cancer pathways using AI as a medical device, DERM.



Following our recent 15M series B funding round and regulatory milestones, we're ready to scale internationally, making history for AI in healthcare and the future of dermatology.



We're proud to epitomise AI for good - with a Class III CE mark, DERM is the only AI as a medical device approved to make clinical decisions autonomously in the cancer space, as well as being the first company to receive a NICE recommendation for use across the NHS.


DERM is deployed at more than 25 NHS organisations where we're supporting dermatology teams to build sustainable services that enable patients to gain quicker access to skin cancer diagnosis. If that's not enough, we also collaborate with some of the largest health insurers to reach patients in their own homes.



We are a team of passionate people on a mission to build a future where no one dies from skin cancer.

The role

Skin Analytics invests in strong evidence for everything we do and we have a pipeline of post-market surveillance and research projects in need of a gifted data scientist.


This role will provide you with the opportunity to contribute to the largest deployments of AI in dermatology conducted to date. Not only are we aiming for our existing technology to be scaled across different populations, but we will also be looking to bring new products to market after comprehensive clinical evaluation. The role reports to our Senior Data Scientist with whom you will work closely on data acquisition, curation and analysis.

(Tech) experience required:

The ideal candidate for this position will possess a Bachelor's degree in a STEM field such as Computer Science, Statistics, Data Science, Engineering or a related discipline, along with proficiency in R or Python for data analysis, manipulation, and basic modelling. Relevant Python libraries include NumPy, pandas (or polars), and Matplotlib; relevant R packages include tidyr, dplyr, and ggplot2. Familiarity with SQL for querying and managing structured data will also be important.


We welcome the use of modern tools--including LLMs--for coding efficiency and productivity. However, it is essential that you're not just running code: you must understand every line of it, review it critically, and ensure it meets our standards for correctness, clarity, and maintainability.

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Responsibilities

Curation, streamlining and management of datasets from both clinical studies and real world deployments. Analysis of publicly available national datasets to support with marketing claims and identification of potential partners Cleaning and management of data sets for training and validation of machine learning algorithms, including maintenance of database Automate workflows for data acquisition To develop code for data analysis results figures and tables whilst meeting appropriate timescales. Design and implementation of dashboards for monitoring of real-world data. This includes visualising insights relating to both the performance of DERM and non-AI related operational insights (e.g. quicksight). These insight may be used to highlight actionable feedback for partner sites or support strategic decision making.

Requirements

Essential Skills

Bachelor's in a STEM field: Computer Science, Data Science, Statistics, Engineering, or a related field Proficiency in R or Python (both preferred) for data analysis, manipulation, and basic modelling Familiarity with SQL for querying and managing structured data Strong attention to detail, with the ability to spot and investigate anomalies in messy datasets (e.g., identifying a missing data point in a consort diagram and tracing its source) Excellent communication skills, in particular, the ability to communicate complex material clearly
Preferred Experience

Exposure to working in a startup or commercial environment (this could include an internship, placement year, or ~1 year of work experience) Postgraduate qualification in a STEM field Familiarity with inferential statistics concepts such as p-values and confidence intervals Experience using version control systems such as Git or GitHub Knowledge of key metrics in diagnostic algorithms such as sensitivity, specificity, positive predictive value (PPV), and area under the curve (AUC) Experience with data visualisation tools: knowledge of tools like PowerBI, Tableau or QuickSight

Benefits

Competitive salary


Bonus structure


Share options package - all our employees have ownership in the company


Private healthcare


25 days annual leave (plus 5 day company shutdown in August + bank holidays)


Enhanced parental leave - includes adoption & foster


Training budget


Weekly catch-ups, monthly meetings to talk about your ambitions and make plans


Lots of fun social activities including company offsite!

Our Values

Building a Strong Foundation


Always Learning


Lead from the Front


Tough and Resilient

The Real Stuff

Skin Analytics embraces and is committed to diversity and equal opportunities. We are dedicated to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be. If you need any changes made to our application process to accommodate your needs, please get in touch with maarty.ramakers@skinanalytics.co.uk




The National Institute for Health and Care Excellence has recommended DERM for use within the NHS until May 2028, while further evidence is gathered*