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Philips
Data Science & AI Lead
Philips
Bengaluru•Hybrid•8-11 Yrs•1 day ago
Job description
HybridLLMData GovernanceAPI IntegrationCloud Technology
Overview
As a Data Science & AI Lead within Philips, you play a key role in translating business challenges into scalable data- and AI-driven solutions.
Responsibilities
- Oversee the performance of AI models, ensuring optimization of algorithms to produce accurate user recommendations, insights, and outputs that align with business objectives and needs.
- Lead statistical analysis and fine-tuning of AI models using test results and validation techniques to validate assumptions, optimize model parameters, and improve predictive accuracy.
- Direct data mining initiatives, including algorithm development, data collection, and preprocessing activities, throughout the design and implementation phases, ensuring high-quality and relevant data.
- Drive the deployment and testing of AI solutions and insights, overseeing implementation efforts, conducting rigorous testing procedures, and validating system functionality and performance.
- Serve as an expert in AI DevOps practices and technologies, shaping methodologies and approaches to effectively manage, automate, and deploy AI models across development and production environments.
- Architect MVP applications that cover the entire lifecycle of AI model development, ensuring scalability, reliability, and performance optimization from initial prototyping to final deployment.
- Evaluate emerging open-source data science and machine learning libraries, assessing their suitability and potential impact on AI initiatives, and recommending adoption strategies.
- Define data needs based on business strategy, developing acquisition plans, data management strategies, and governance frameworks to ensure data availability, quality, and integrity.
- Oversee the performance of the data and AI team, providing leadership, direction, and support to ensure the successful execution of projects, alignment with goals, and professional development.
- Manage talent across the team, while driving employee selection, performance management, compensation management, career development, and ensuring effective operational management.
- A Bachelor's / Master's Degree in Computer Science, Information Management, Data Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or equivalent.
- Minimum 8 years of experience in areas such as Data Handling, Data Analytics, AI Modeling or equivalent.
- Thorough understanding of the Azure stack and preferably AWS.
- Proven experience in design and execution of exploratory data analyses and in generation of data insights
- Proven experience in design and implementation of data solutions based on LLM, ML and/or GenAI.
Qualifications
- Statistical Methods
- Data Harmonization & Processing
- Model AI technologies (LLM, Agentic AI)
- Algorithm Development
- Azure DevOps
- Data Governance
- API Integration
- Data Engineering
- Regulatory Requirements
- Stakeholder Management
- Cloud technology, preferably acquainted with both AWS and Azure
- Learn more about our business.
- Discover our rich and exciting history.
- Learn more about our purpose.
Nice to have
- Statistical Methods
- Data Harmonization & Processing
- Model AI technologies
- Regulatory Requirements
- Stakeholder Management