Senior Expert Data Science

Novartis; Barcelona; Híbrido; EUR 43.000 - 79.000; Jornada completa

Descripción de la vacante

Novartis in Barcelona, Spain, is seeking a Data Scientist to join our hybrid team. You will manage projects, work across data sources, and develop advanced analytics to support medical and business decisions.

The role emphasizes Python, AI/ML techniques, and collaboration across functions to deliver scalable solutions. English communication is essential in this globally oriented group.

Formación

• 4+ years of relevant experience in Data Science.
• Track record delivering global solutions at scale.
• In-depth knowledge of Artificial Intelligence (AI) and Machine Learning.
• Python proficiency at a professional level.

Responsabilidades

• Project manage own tasks and collaborate with allied team members; plan proactively and manage changes.
• Understand life science data sources including preclinical, clinical, sales, contracts, promotions, and Real World Evidence.
• Research and co-develop data management methods, algorithms, and models; provide insights from structured and unstructured data.

Conocimientos

Data Science

Python

English (Professional)

Cross-functional collaboration

AI / ML knowledge

Descripción del empleo

Salary Range:
€42,600.00 - €79,200.00

Job Description Summary

#LI-Hybrid

Location: Barcelona, Spain

Relocation Support: This role is based in Barcelona, Spain. Novartis is unable to offer relocation support. Please apply only if this location is accessible.

Key Responsibilities

• Project manage own tasks and works with allied team members; plans proactively, anticipates and actively manages change, sets stakeholder expectations as required, identifies operational risks and drives issues to resolution, minimizes surprise escalations, with initial support from supervisors
• Understand life science data sources including preclinical, clinical, sales, contracting, promotions, social media, patient claims and Real World Evidence
• Research and co-develop with supervisor in data management, new algorithms, methods, statistical models and business models and providing insight into structured and unstructured data
• Support the evaluation of the need for technology and novel scientific software, visualization tools and new approaches to computation to increase the efficiency and quality of the Novartis practices
• Independently identifies research articles and proposes them for application to Novartis business problems
• Develop automation for data management, repeatedly refreshing analysis and generating insights
• Understand complex and critical business problems, formulates integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute to solving unmet medical needs, discover actionable insights, and automate processes for reducing effort and time for repeated use.
• Manage the implementation and adherence to the overall data lifecycle of enterprise data from data acquisition or creation through enrichment, consumption, retention, and retirement, enabling the availability of useful, clean, and accurate data throughout its useful lifecycle.
• High agility to be able to work across various business domains. Integrate business presentations, smart visualization tools and contextual storytelling to translate findings back to business users with a clear impact.

Essential Requirements

• 4+ years of relevant experience in Data Science
• Track record delivering global solutions at scale.
• In-depth mastery of external environment and trends
• In depth knowledge of Artificial Intelligence (AI), Machine Learning
• Experience in Python is a must
• Professional level of English, both written and spoken
• Strong collaboration skills and ability to work effectively across functions and teams.

Commitment to Diversity & Inclusion

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Skills Desired

• Agentic AI, Agentic AI, Artificial Intelligence (AI), Artificial Intelligence Technologies, Biostatistics, Business Mindset, Change Management, Change Management Processes, Curious Mindset, Data Governance, data governance and management (Inactive), Data Literacy, Data Quality, Data Quality Management, Data Science, Data Visualization, Deep Learning, Deep Learning Algorithms, Digital Literacy, Generative AI, Graph Algorithms, Learning Agility, Learning agility, being curious (Inactive), Logistic Regression Model (Inactive), Machine Learning (ML) {+ 14 more}