Junior Healthcare Data Analyst

Location: Porto, Porto District, Portugal

Workplace: hybrid

Employment Type: full

Description

Learn about knok

At knok, we dare to lead and humanise the digital transformation of healthcare. We envision a world where everyone has timely access to quality healthcare through digital technology, creating a more equal society. We genuinely believe in it, and you can recognise it in every person who embraces this mission.

Through a Digital Front Door strategy, knok connects patients, providers and healthcare professionals in one place. Our API-first white-label platform enables a continuous, engaging and personalised healthcare experience for all conditions through a cutting-edge Patient Journey Engine.

With regular clinical practice as our main source of knowledge, we leverage ready-to-use data to improve care automation and increase financial savings. Since 2015, we have enabled more than 2.5 million clinical interactions in over 12 countries. Our platform is scalable and AI-ready, enhancing the power of data-driven care to deliver better outcomes during all stages of life.

Are you ready to join us in revolutionising healthcare and making a tangible impact on peoples lives?

About the role

We are looking for a Junior Healthcare Data Analyst to support our teams in turning complex healthcare data into meaningful insights. You’ll be working with datasets from different sources, such as clinical operations, insurance processing, and patient journeys - helping us improve care delivery and decision-making.

If you’re passionate about using data to make healthcare more accessible and effective, dont stop here - dive deeper!

As an Junior Healthcare Data Analyst, you will:

• Collect, clean, and analyse healthcare data from multiple sources (e.g. EHR, patient demographics, operational systems), to extract meaningful insights;
• Develop and maintain dashboards, reports, and visualisations to communicate key metrics and findings to stakeholders, including clinicians, operational teams and leadership team;
• Collaborate cross-functionally with teams across the organisation, including data science, product management, and clinical operations, to support data-driven decision-making;
• Perform statistical analysis to support population health management, risk stratification, and clinical outcome optimisation;
• Contribute to improving data quality by identifying data quality issues and anomalies, and work with relevant stakeholders to address and resolve them.

What makes you a great fit for this journey

• Bachelors degree in Biomedical Engineering, Medical Statistics, Biomedical Sciences, Data Science, Statistics, Computer Science, Health Informatics, or a related field. Masters degree preferred;
• Experience (academic or professional) with data visualisation tools such as Tableau, Power BI or similar;
• Technical expertise regarding data models, database design development, data mining and segmentation techniques;
• Ability to turn complex data into clear insights that support better decision-making;
• Knowledge of programming languages such as Python or R for data analysis and statistical modeling;
• Ability to explain a dashboard or an analysis to someone without a technical background, in a simple and practical way;
• Care when working with data to ensure accuracy, consistency and reliability;
• Ability to manage several analytical tasks at the same time, prioritising what has the greatest impact on the business and patients.

Nice to have:

• Experience with SQL;
• Experience with Apache Superset;
• Previous experience or exposure to the healthcare sector.

Recruitment stages

1. People Interview: A conversation to get to know you better, explore your background and motivation, and introduce you to knok, our culture, and the role.
2. Case Study: A practical exercise designed to understand how you approach data, structure your analysis, and turn information into meaningful insights.
3. Final Interview: A conversation with the Hiring Manager where youll present your case study, explain your reasoning, and discuss your approach in more detail.