Role Summary

Do you want to make a global impact on patient health? Do you thrive in a fast-paced environment that integrates scientific, clinical, and commercial domains through engineering, data science, and AI? Join Pfizer Digital’s Artificial Intelligence, Data, and Advanced Analytics organization (AIDA) to leverage cutting-edge technology for critical business decisions and enhance customer experiences for colleagues, patients, and physicians. Our team of engineering, data science, and AI professionals is at the forefront of Pfizer’s transformation into a digitally driven organization, using data science and AI to change patients’ lives. The Data Science Industrialization team is a key driver of Pfizer’s digital transformation, leading process and engineering innovations to advance AI and data science applications from prototypes and MVPs to full production.

As a Manager, AI and Data Science Full Stack Engineer, you will join the Data Science Industrialization team. Your responsibilities will include architecting and implementing AI solutions at scale for Pfizer. You will iteratively develop and continuously improve data science workflows, AI based software solutions, and AI components.

Role Responsibilities

• Develop end-to-end data engineering, data science and analytics products and AI modules.
• Develop server-side logic using back-end technologies such as Python.
• Develop data ETL pipelines using python and SQL.
• Create responsive and visually appealing web interfaces using HTML, CSS, and Bootstrap.
• Build dynamic and interactive web applications with JavaScript frameworks (React, Vue, or AngularJS)
• Build data visualizations and data applications to enable data exploration and insights generation (e.g, Tableau, Power BI, Dash, Shiny, Streamlit, etc.).
• Implement and maintain infrastructure and tools for software development and deployment using IaC tools
• Automate processes for continuous integration, delivery, and deployment (CI/CD pipeline) to ensure smooth software delivery
• Implement logging and monitoring tools to gain insights into system behavior.
• Collaborate with data scientists, engineers, and colleagues from across Pfizer to integrate AI and data science models into production solutions
• Demonstrate a proactive approach to identifying and resolving potential system issues.
• Contribute to the best practices of the team and help colleagues grow
• Communicate complex technical concepts and insights to both technical and non-technical stakeholders.
• Stay up-to-date with emerging technologies and trends in your field.

Qualifications

Must-Have

• Bachelor's or Master's degree in Computer Science, or a related field (or equivalent experience).
• 5+ years of experience in software engineering, data science, or related technical fields.
• Proven experience as a Full Stack Engineer or similar role, with a strong portfolio of successful projects.
• Solid experience in programming languages such as Python or R, and experience with relevant libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Good understanding of back-end technologies, databases (SQL and NoSQL), and RESTful APIs.
• Knowledge of BI backend concept like Star Schema and Snowflake
• Experience in building low code dashboard solution tools like Tableau, Power BI, Dash and Streamlit
• Highly self-motivated, capable of delivering both independently and through strong team collaboration.
• Ability to creatively tackle new challenges and step outside your comfort zone.
• Strong English communication skills (written and verbal)

Nice-to-Have

• Advanced degree in Data Science, Computer Engineering, Computer Science, Information Systems or related discipline
• Experience in CI/CD integration (e.g. GitHub, GitHub Actions) and containers (e.g. docker)
• Experience developing dynamic and interactive web applications; familiar with React, AngularJS, Vue.
• Experience in creating responsive user interfaces; familiar with technologies such as HTML, Tailwind CSS, Bootstrap, Material, Vuetify
• Experience with Infrastructure as Code (IaC) tools such as Terraform, Ansible, or Chef
• Proficiency in Git for version control of infrastructure code and application code
• Familiarity with monitoring and observability tools such as Prometheus, Grafana, or ELK stack
• Knowledge of serverless computing and experience with serverless platforms like AWS Lambda.
• Good knowledge of data manipulation and preprocessing techniques, including data cleaning, data wrangling and feature engineering.
• Good understanding of statistical modeling, machine learning algorithms, and data mining techniques.
• Experience with data science enabling technology, such as Dataiku Data Science Studio, AWS SageMaker or other data science platforms
• Familiarity with cloud-based analytics ecosystems (e.g., AWS, Snowflake).
• Hands on experience working in Agile teams, processes, and practices

Work Location Assignment:Hybrid