Understands complex and critical business problems from a variety of stakeholders 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. 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 transforming the way to solve a problem using Data Science and Artificial Intelligence.
• Articulates solutions /recommendations to business users. 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 stakeholder expectations as required, identifies operational risks and enable the team to drives issues to resolution, balances multiple priorities and minimizes surprise escalations
• Collaborates with internal stakeholders, external partners and Institutions and cross-functional teams to solve critical business problems, propose operational efficiencies and innovative approaches.
• 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, guidance 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 stakeholders including senior business leaders. Contribute to the development of Novartis data science capabilities.May lead a Team / Function or 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 and Distribution of marketing samples (where applicable)

Education & Qualifications

• Bachelor’s degree in computer Sc. or IT related field or technical discipline

Experience

• Minimum of 10 years of experience in the field of Data Science, with a strong background in Big Data.
• Proficiency in cloud platforms such as AWS and Azure is a must, as well as expertise in SQL and Python programming languages. The candidate should also have a solid background in data visualization, enabling them to effectively communicate complex insights to stakeholders.
• A strong understanding of full-stack development is highly desired. Familiarity with ML ops (Machine Learning Operations) is also important, as the candidate should be experienced in deploying and maintaining machine learning models in production environments. Experience with AI technologies, including tools like GenAI2, is considered a plus.
• The candidate should have a track record of working on practice cases, showcasing their problem-solving skills and ability to apply technical expertise to real-world scenarios. Continual professional development and a passion for learning are valued traits, as the candidate should be eager to take on new challenges and further enhance their skills in the field of Data Science.