* Envision, develop, and oversee the implementation of ethical and responsible AI/ML practices across the enterprise* Evaluate the landscape of innovation in AI/ML across industries, and develop a strategy to bring them to bear with respect to Pfizer’s organizational needs and strategic vision * Lead data science work streams in broader organizational initiatives by providing operational support as well as thought leadership on technical and strategic objectives* Directly engage and communicate with key business and technical stakeholders in cross-functional teams to influence and advance enterprise-wide initiatives, and take charge for planning and completion of project milestones and deliverables* Consult and lead execution on data science projects using rigorous statistical methods and machine learning techniques* Manage junior team members through technical and organizational thought leadership and innovation* Design, develop, deploy and maintain reusable assets and custom pipelines to optimize operational efficiencies in analytics execution* Research, identify, and apply new algorithms, technologies, and frameworks to solve scientific, clinical, and business problems

Process and clean raw data to make it suitable for algorithm development and model training. This may include operations such as data cleaning, feature extraction, data transformation, etc.Develop, train, validate, and evaluate machine learning models or other related models. This may involve feature engineering, model selection, hyperparameter tuning, etc.Implement the developed algorithms and models into real systems, integrating with other components. This may require writing code, API integration, performance optimization, etc.Evaluate algorithms for performance, efficiency, and accuracy, and optimize them to meet specific requirements. This may involve algorithmic complexity analysis, parallelization, resource utilization optimization, etc.

Designing and developing data storage solutions, such as data warehouses, data lakes, or NoSQL databasesBuilding and maintaining ETL (Extract, Transform, Load) pipelines that move data from various sources into the organization's data storesWriting code to automate data processing tasks and data quality checksEnsuring data security, privacy, and compliance with regulations such as GDPR or HIPAACollaborating with data analysts and data scientists to understand their data requirements and provide the necessary infrastructure and toolsEvaluating and recommending new data management technologies and tools.

1. Responsible for designing and implementing data pipelines to extract, transform and load data from various sources (such as databases, log files, sensors, etc.) into data warehouses, data lakes or other target systems. These pipelines are developed and maintained using programming languages such as Python, Java or Scala and ETL (Extract, Transform and Load) tools.2. Data warehouse and data lake: Responsible for building and maintaining data warehouse and data lake, which are key components for storing and managing large amounts of data. Design data models, optimize query performance, and ensure scalability and security for data warehouses and data lakes.3. Data Quality and Data Governance: Responsible for ensuring the quality and consistency of data. Develop and implement data quality checks and cleansing processes, handle outliers and missing values in data, and work with data owners and relevant departments to ensure data compliance and accuracy.

1. Software Development: Use programming languages and development tools to implement software functionality and follow coding standards and best practices.2. Programming and debugging: programming and debugging to ensure the correctness and stability of the software. Analyze and fix bugs and problems in software, conduct unit testing and integration testing to ensure the quality of software.3. Software design: Participate in the design and architecture of software systems. Design software modules, components, and interfaces based on requirements and functional specifications, and ensure software scalability, maintainability, and