Posició: Enginyer/a
Ubicació: Barcelona (Espanya)
Tipus de Contracte: Indefinit
Jornada: Jornada completa
Sector: Farmacèutica i biofarmacèutica
Vacants: 1
Salari: 33000/46000€ Brut/anyDisciplina: I+D
Modalitat de treball: HíbridaBARCELONA ACTIVA gestiona ofertes d'empreses que necessiten cobrir vacants de personal. Les posicions que es publiquen no són per a Barcelona Activa. NOMÉS ES TINDRAN EN COMPTE LES CANDIDATURES QUE ARRIBIN PER AQUEST CANAL. El Servei de Cerca de Treballadors/es s'adreça a aquelles empreses del territori que necessiten incorporar nous professionals als seus equips i ofereix suport en la identificació de les vacants, el reclutament de personal i la preselecció de candidatures que s'ajustin als perfils sol·licitats.
An innovative Research and Development company is seeking a Data Scientist to join its team and lead the technical aspects of developing a cutting-edge breast cancer diagnostic device.
We are looking for a highly skilled, collaborative, and innovation-driven professional passionate about advancing healthcare solutions.
Key Responsibilities:
Lead improvements in AI algorithms based on clinical exam data collected with the device, prioritizing sensitivity and specificity for the most challenging classes.
Design and implement preprocessing pipelines: signal noise removal, normalization, scaling, and feature extraction.
Maintain and update our comprehensive dataset, addressing data scarcity challenges.
Drive problem-solving initiatives and provide technical expertise to address complex AI model development issues.
Collaborate with the Head of Engineering and Chief Clinical Officer to optimize the quality of collected data readings.
Work alongside the Head of QA/RA to ensure all technical development aspects comply with quality standards, regulatory requirements, and industry best practices.
Requirements:
Higher Degree in Computer Science, Bioinformatics, Physics, Mathematics, or a related field.
Minimum of 3 years of hands-on experience in developing preprocessing algorithms for multidimensional time series classification.
Expertise in cross-validation strategies and handling class imbalance.
(Preferred) Knowledge of electronics and sensor signal acquisition.
Strong collaborative mindset, open to iterative model refinement based on feedback from engineers and clinicians.
Core Competencies:
Leadership
Self-confidence
Teamwork and Cooperation
Learning and Application of Knowledge
Commitment to the Organization
Planning and Organization
Achievement Orientation
Communication Skills
Strategic Thinking
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