Description de l'offre
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
Minimum education: University degree in Statistics, Operational Research, Computer Science or in a highly quantitative field Fluent English written & spoken
Work experience: 5+ years post-graduate experience in a multidisciplinary data & analytics environment or in research; 3+ years in predictive modeling and large data analysis
Mobility: Candidates looking for an international career, open to relocate to different countries and with a global mindset
Technical competencies: Experience in statistical/analytics tools such as R, SAS, Python or big data technologies for machine learning. Expertise in at least a visualization tools Qlikview, Spotfire, Tableau for designing insights. Expertise in working with data bases and hands of experience with data mining – concepts, techniques, implementation. A track record of innovating through machine learning and statistical algorithms and their applications. Practical experiences with data discovery with large and complex data assets from varied information sources
Professional competencies: Proven self-starter with experience in initiating and ensuring delivery. Ability to adjust to multiple demands, shifting priorities and unexpected events while maintaining a positive work attitude. Well-organized, excellent time management with respect to priorities and self-management. Strong interpersonal and communication skills, and ability to communicate analytical and technical content with clarity to non-experts. Expert team player with demonstrated ability to build collaborative relationships. Quick action taker. Result driven and proactive attitude with high commitment. Self-motivated with a high degree of ownership and accountability for results
Barcelona Gran Vía
Audit & Finance
Novartis Farmacéutica, S.A.