Data Manager Aidence
AI-powered clinical applications for lung cancer diagnostics and treatments.
Permanent
Paris
Remote: Not specified
45K to 55K € a year
> 3 years
Skills we're looking for
Attention to detail
Continuous improvement
Safety protocols knowledge
Communication skills
Adaptability
+6
You'll be part of
14 employees
Intelligence artificielle / Machine Learning
Our take
The medical technology market is expected to continue its growth due to innovative technological developments, the increasing pace of population ageing, chronic diseases, and trust in medical devices. Alongside this, advancements in AI and robotic solutions, cloud-based software and healthcare apps, are likely to boost industry growth in the future. Radiologists agree that AI is necessary to compensate for the increase in medical images they need to assess. Without AI, the demand for scans would outgrow the human ability to review them timely and accurately. Aidence provides an AI solution for lung nodule detection and management, which helps improve lung cancer prognosis by detecting, measuring, classifying and tracking the growth of pulmonary nodules on patients' chest CT scans. Aidence was acquired by US radiology firm RadNet in 2022. Its future goals include expanding its products to detect larger masses on chest CTs and using the data collected from scans to provide further insights into the effectiveness of lung cancer treatments.
You'll be working on
- Data is a strategic asset at every phase of product development, and the Data Team’s role is to put it at the center of all stakeholders’ workflows
- The Associate Data Manager will join a team that has built solid experience managing multiple products in parallel, with shared tooling and processes across products and modalities
- The team’s pipelines continue to evolve to meet new challenges like data export and dataset creation
- Strong bridges with our AI and Software teams fuel constant knowledge sharing and technical upskilling
- As a member of the Data Team, the Associate Data Manager will collaborate closely with Radiologists, Product Managers, AI Engineers, Clinical Research Scientists and Software Developers to build and improve our medical products
- Design and maintain efficient tooling (pipelines, dashboards, automation) for the Data Team itself as well as for any stakeholder who needs to access, explore, or leverage the data
- Surface actionable insights from the data lake by identifying, structuring, and delivering relevant information to stakeholders across product, AI, and clinical teams
- Join at least one squad and be the Data expert
- Participate in the targeting and collection of relevant data
- Build and structure medically consistent and representative datasets
- Establish relevant annotation guidelines and training to ensure annotation quality
- Be a stakeholder in the ongoing overseeing and refinement of AI algorithm performances.
- PLEASE NOTE: This is not an exhaustive list of all duties, responsibilities and requirements of the position described above. Other functions may be assigned and management retains the right to add or change duties at any time
We're looking for
- Knowledge of medical imaging. (Preferred)
- Able to manage multiple topics in parallel while maintaining a big-picture view. (Required)
- Proactive and curious, with a continuous improvement mindset. (Required)
- Proficiency in a programming language (ideally Python) and comfortable working with databases (BigQuery, MongoDB). (Required)
- Strong reasoning abilities and attention to detail. (Required)
- Good communication skills — able to translate needs between technical and less technical stakeholders. (Required)
- Driven to solve medical problems. (Required)
- Machine learning understanding. (Preferred)
- Analytical and scientific mindset. (Required)
- Master’s degree in a health-related field required
- Experience building internal tools or data pipelines. (Preferred)
- Ability to structure, document, and industrialize data processes. (Required)
- Follows all DeepHealth policies and procedures
- Follows data privacy, compliance, safety and confidentiality standards at all times
- Practices universal safety precautions
- Reports to work regularly as scheduled; consistently punctual with respect to working hours, meal and rest breaks, and maintains satisfactory personal attendance in accordance with DeepHealth guidelines
- Promotes good public relations on the phone and in person
- Demonstrates initiative, personal awareness, professionalism and integrity, and exercises confidentiality in all areas of performance
- Follows all local, regional and country laws concerning employment
- Communicates, cooperates, and consistently functions professionally and harmoniously with all levels of supervision, co-workers, visitors, and vendors
- Completes job responsibilities in a quality and timely manner
- Adapts and is willing to learn new tasks, methods, and systems