IT DIRECTOR DATA SCIENCE & ANALYTICS (AWS)

Summary Location.
Barcelona (Hybrid) Novartis is unable to offer relocation support for this role.
please only apply if this location is accessible for you.
We are currently seeking a talented Data Science Director who will be responsible for overseeing and driving the delivery of business solutions and services at an enterprise level within a global sub-domain.
This role will involve managing projects and operations in the specified sub-domain, ensuring end-to-end project delivery and operational excellence.
The Data Science Director will collaborate with business stakeholders, Global Business Units, and TT Strategic Business Partners to analyze demand, propose and evaluate solutions, and ensure successful project delivery.
About the Role Major accountabilities.
Act as the primary connection between Finance end to end Solution delivery and the Digital business for a given capability Analyse and refine requirements for delivering the necessary technology service to business Solution Design of Finance system solutions in alignment with design and architectural standards, while meeting quality, performance, security and business requirements.
Manage project teams in different locations.
Own and Drive the end to end Technical Product Delivery.
Ensure IT services are aligned with business strategy, business objectives, business requirements, standards and regulations Understand the processes, plans, objectives, drivers, and issues related to the business capability, as well as the appropriate external policies and regulations.
Identify and qualify new demand with overall responsibility for steering proposals through the early phases of approval Significantly contribute and drive multi-year, large-scale product roadmaps for key finance processes on global & headquarter core applications with significant impact on Novartis financial results Provide IT consulting to the capability stakeholders, educate them on IT processes and methodologies and drive adoption of global solutions Ensure digital technology impact analysis is provided to business Initiate and drive projects from conception to completion with minimal guidance.
Establishes scalable, efficient, automated solutions for large scale data analyses, model development, model validation and model implementation.
Communicate complex data or algorithms into simple conclusions that will empower leadership to drive action based on the insights you derive.
Collaborate in multi-functional teams to evaluate business activities, and then develop innovative and effective approaches to tackle team’s analytics problems and communicate results and methodologies.
Develop and maintain infrastructure for machine learning models in production Monitor and optimize machine learning models for scalability, performance, and reliability Implement and manage continuous integration and delivery pipelines for machine learning products  Collaborate with data scientists and ML engineers to ensure smooth integration of models to production environment Minimum Requirements.
Work Experience.
University working and thinking level, degree in technical computer science or information security area or comparable education/experience 8+ years of relevant professional IT experience in the related functional area.
Experience of running ML solutions in production, making the data accessible and maintaining a Data Science platform (cloud based on AWS, Azure, GCP) You are a problem solving, hands-on and analytical personality, a strong team player with solution orientated and initiative-taking mindset.
Demonstrated ability in the establishing of MLOps practice and associated practices in complex environments.
Experience in coaching and leading agile dev teams, and building a team and culture around agile development practices.
Deep, hands-on technical and operational expertise with IT technologies like.
Snowflake, DB design / modelling, Databricks Airflow or equivalent data orchestration tool Bitbucket or equivalent source code repository tool AWS foundational.
Demonstrated experience AI scalable solutions industrialization, establishing the vision for major products.
Experience interacting and influencing cross-functional stakeholders to execute high-impact projects.
Experience developing CI/CD pipelines for AI/ML development, deploying models to production, and managing the lifecycle in a regulated environment.
Hands-on experience in development, deployment and agile life cycle management of data science apps (MLOps).
Languages.
English.