Summary

Understands complex and critical business problems from a variety of customers and business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To manage the definition, 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 usefull 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.Independently set strategy, manage budget, ensuring appropriate staffing and coordinating projects within the area supervised. If managing a team: empowers the team and provides guidance and coaching, with limited guidance from more senior managers.

• Innovate by redefining the way to solve a problem using Effective data management, Data Science and Artificial Intelligence.
• Articulates solutions /recommendations to business users.
• Provides pathways to manage data effective for analytical uses.
• Presents analytical content concisely and effectively to non-technical audiences and influences non-analytical business leaders to drive major strategic decisions basis analytical inputs -Coordinates, prioritize and efficiently allocates the team resources to critical initiatives: plans resources proactively, anticipates and actively manages change, sets customer expectations as required, identifies operational risks and enable the team to drives issues to resolution, balances multiple priorities and minimizes surprise critical issues -Collaborates with internal customers, external partners and Institutions and cross-functional teams to solve critical business problems, propose operational efficiencies and innovative ways.
• Proactively evaluates the need of technology and novel scientific software, visualization tools and new approaches to computation to increase efficiency and quality of the Novartis data sciences practices -Provides agile consulting and non-standard exploratory analysis for unplanned urgent problem -Independently identifies research articles and reproduce / apply methodology to Novartis business problems -Publishes in peer reviewed journals, helps organizing sessions at external professional conferences and contributes to cross-industry work streams in external relevant working group -Makes right choices from a breadth of tools, data sources and analytical techniques to answer a wide range of critical business questions -Ensures exemplary communication with all customers including senior business leaders -Contribute to the development of Novartis data management and data science.
• In-depth technical expertise in a scientific / technical field depending upon the career path (Manager/Individual contributor) -Reporting of technical complaints / adverse events / special case scenarios related to Novartis products within 24 hours of receipt -Distribution of marketing samples (where applicable).

• 10+ years of relevant experience in Data Science.
• Experience of Apache Spark, Artificial Intelligence (Ai), Big Data, Data Governance, Data Literacy, Data Management.
• Knowledge of Python (Programming Language), R (Programming Language).

• Graduate / Post Graduate in Engineering or equivalent