The Advanced Analytics Manager Finance is responsible for the capabilities needed to operate a financial and business practice using advanced techniques to understand data and produce insights that are of value to Novartis. The mission is to solve financial and business challenges applying Advanced Analytics and Data Modelling techniques on a variety of small, medium and big data. The Advanced Analytics Manager Finance will drive the development and implementation of advanced forecasting techniques to support key financial processes such as budget, strategic planning, latest outlook. The Advanced Analytics Manager Finance will develop methodologies to identify and quantify drivers that impact the financial performances, with the perspective to optimize resource allocation decisions. The Advanced Analytics Manager Finance will be key link in connection between country organizations and IT data scientists. She or he will need to understand the business questions from country organization and translate into technical guides and instructions to IT data scientists. The role encompasses the full lifecycle from ideation to requirements elicitation, design, implementation and rollout of the solutions. She or he will work and interact actively with internal stakeholders across different functions and department at country, region and global levels, as well as external ones, such as consultants, universities, etc.
• Primarily responsible to lead and drive advanced analytics activities in finance, including explorative applications of machine learning, deep learning and artificial intelligence. • Ensure smooth performance of implemented models and on-time delivery of machine-generated forecasts. • Excellent quantitative skills and the ability to tell a story using data. • Strong familiarity and experience with data preparation and processing such as assessment of data quality, new variable creation, variable selection, etc. • Ability to create advanced predictive models using concepts like Time Series, Regression techniques, Artificial Neural Networks, Random Forest, etc. • Experiment with new datasets to try unguided and unsupervised learning to understand hidden insights. • Ability to build and fine tune algorithms that scale up from small-scale proof-of-concept stage to full production systems -Build knowledge artifacts of real business problems that were solved with advanced analytics techniques which can be published in journals. • Drive Innovation ideas / discussions, PoC’s. Evaluate new technological developments and evolving business requirements and makes recommendations for improved service levels and efficiencies. • Provide input to project proposals related to new technologies/innovations. Actively engage with internal and external business & technical stakeholders. Structure problem domain and drive/define data, process, functional, and architectural requirements. • Be ultimately accountable for the full lifecycle of the advanced analytics solution. • Work with relevant partners in functions or franchises to scope data science requirements: need identification, hypothesis generation, data discovery and methodology proposal. • Select and rapidly prototype the models that are appropriate for the problem at hand and the available data that characterizes the components of the problem. • Responsible for recommending the most appropriate data science approach to ultimately solve the problem at end. • Ensure the selected data science approach can be engineered in an advanced analytics product.
• Ensure projects that use external data science consultants or solution vendors are well managed by ongoing engagement.
Barcelona Global BPA Team, Advanced Analytics Lead