Expert Data Scientist
To add even greater value for the business we need to have the right people with the right capacities in the right location. We need ground-breaking innovation, customer-orientation and focus on bringing the best services and solutions to the business – both globally and locally – to support Finance.
We are looking for early talent with experience in consulting or business partnering who are eager to make a difference.The hub offers a real opportunity to develop in a highly fast-paced, multicultural, technology-driven environment where collaboration and innovation are at the heart of who we are and what we do.Job DescriptionYour responsibilities include, but not limited to:Translate business questions into analytical problems and build solutions using visualization techniques, machine learning, and statistical modeling.Search and develop new algorithms, methods, statistical models and business models, providing insight into structured and unstructured data.Quickly learn and pilot the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions and to improve status quo.Identify research articles and reproduce/apply innovative methodology to Novartis business problemsProvide understandable and meaningful business intelligence for key partners.Bring understanding of one or more areas of data science and demonstrate practical knowledge of techniques.Help developing new quantitative methods with the aim of improving processes in various projects and developing new analysis opportunities by integrating existing and new data sources.Support various projects, of limited scope.Role Requirements:Degree in Mathematics, Statistics, Computer Science, Physics or in a quantitative field.Academic experience in a multidisciplinary data & analytics environment or in researchExperience in predictive modelling and large data analysis.Experience in PythonExperience in SQLA track record of innovating through machine learning, data bases and statistical algorithms and their applications.Strong analytical and problem-solving skills.Hands-on experience with data mining, its concepts, techniques and implementation.Ability to work collaboratively in a team environment, aligning decisions and developments with data engineering, software development, MLOps, visualization and business teams.Excellent communication and presentation skillsFluent English (written and verbal)Desirable requirements:Knowledge on cloud computing (AWS)Knowledge on version control systems (GIT)Knowledge on project management tools (Jira)Why consider Novartis?We believe the answers are found when curious, courageous and collaborative people like you are brought together in an inspiring environment.
Where you’re given opportunities to explore the power of digital and data. Where you’re empowered to risk failure by taking smart risks, and where you’re surrounded by people who share your determination to tackle the world’s toughest medical challenges.Imagine what you could do at Novartis!Commitment to Diversity & Inclusion:Novartis embraces diversity, equal opportunity and inclusion.We are committed to building diverse teams, representative of the patients and communities we serve, and we strive to create an inclusive workplace that cultivates bold innovation through collaboration, and empowers our people to unleash their full potential.Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to learn more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/networkSkills DesiredAnalytical Thinking, Applied Mathematics, Curious Mindset, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning, Machine Learning (Ml), Machine Learning Algorithms, Master Data Management, Python (Programming Language), Sql (Structured Query Language), Statistical ModelingSummaryLocation: Barcelona Gran VíaType: Full time