🩺 At Lifen, we believe that everyone deserves high-quality, accessible, and financially sustainable healthcare(e)Lifen’s digital solutions are the missing puzzle piece for a truly patient-centric care system(e)We build bridges between stakeholders by facilitating the information flow: providers, insurance companies, governments, patients and the most innovative digital health apps.
🔗 How? We solve the interoperability puzzle so digital health innovators and healthcare facilities don't have to(e)Our FHIR platform helps cloud-based apps integrate seamlessly with primary data systems, without the hassle of connector jigsaws.
🔮 Lifen is also a pioneer in Artificial Intelligence: we build algorithms that reliably and automatically structure and integrate health information for a truly complete and dependable record system, eliminating hundreds of thousands worth of hours of routine administrative tasks.
Born in Paris and reborn all over Europe, we are more than 180 Lifeners committed to bringing the digital revolution to the healthcare sector.
Lifen is always on the lookout for new talent 👱🏼♀️🧑🚀
The Data Analyst Team is responsible for defining the KPIs and making them available to all the company's teams(e)He also participates in the development of the Data strategy to make the whole company more data-driven.
The team have both internal and external stakeholders: our clients, final users, internal users(e)Our internal customers are quite varied (product, support, marketing, finance, business, roperations, c-leves etc.)
Data Analysts are a key part of the Data team(e)They are the one directly responsible for enabling the data strategy(e)This includes serving the right data to both internal and external clients, as well as implement and maintain data products to be used by other analysts.
Your future Missions as a Senior Data Analyst
Operational Missions
- Use reporting tools to generate standard or custom reports to summarize business, financial, or economic data and prepare custom reports for review by executives, managers, clients, and other stakeholders.
- Maintain and scale our existing data pipelines with the Data engineering Team
- Develop interactive visualizations allowing operational metrics to be summarized at an organizational level and/or presented at team/individual levels
- Testing of newly developed features, help to maintain a good automatic testing coverage
Strategic Missions
- Collaborate with business stakeholders to deliver on business intelligence needs and contribute to our data analytics platform and maintain data integrity/quality
- Manage timely flow of business intelligence information to users to ensure that project documents are complete, current, and elaborate and stored appropriately
- Establish a deep understanding of our business and customer; leverage data to provide insights about our customer, product, markets and competitors
Mentoring Missions
- Ensure good onboarding of newcomers within the Core-Teams and possibly V-Teams.
- Mentor more “junior” profiles within the team, help them thrive and progress in the organisation.
- Ensure a good technical watch, share useful information, new piece of tech, framework that can make our products better
The profile we're looking for
- Strong proefficiency with SQL, Data visualization/business intelligence tools (Looker, Tableau, Metabase, PowerBI etc..)
- Excellent written and verbal communication skills, especially in translating business requirements/objectives into technical specifications
- Knowing her way around an agile environment is important
- Experiences in one or more Data Engineering tools : Airflow, DBT, AWS products…
- Experience in one or more object oriented language (Python)
- Team spirit and ability to work in a team composed of different profiles (developers, QA, Product, Infra…)
- Know how to share its knowledge and help more junior profiles thrive.
- Can give and receive feedbacks from its peers, managers and managees(e)Ability to spot strengths and areas of improvements in others.
- Strong problem-solving approach
About our hiring process
- HR Interview with Satyane
- Interview with the Managers
- Technical Test with 1 member of the team
- Interview with Data team members
- Reference Check