About the role

AI summarised

As a Senior Data Scientist at GlobalFoundries, you will collaborate with lead data scientists and business stakeholders to develop, deploy, and maintain scalable predictive and prescriptive analytics solutions. You will support data pipeline creation, conduct exploratory analysis, build and tune machine learning models, and help deploy and monitor models in production. You will also contribute to team capability building and communicate analytics value to fab leadership and partners.

FoundryOnsite

Key Responsibilities

Work closely with Lead Data Scientists and business customers to translate their needs into predictive and prescriptive analytics solutions
Collaborate closely with GFIT, Manufacturing Data Domain group to support Lead Data Scientist in building the required data pipelines for productionalized and scalable predictive and prescriptive analytics solutions
Support Lead Data Scientist to conduct exploratory data analysis and create compelling visualization using complex and high-dimensional datasets
Help Lead Data Scientist to identify suitable machine learning or statistical approaches on type of problem and train models for optimal performance, including hyperparameter tuning
Contribute to deploy models into production with assistance from Product Engineers
Help Lead Data Scientist to validate and monitor models to ensure consistent performance and avoid performance degradation
Support Lead Data Scientist during technical and analytics capability building within the analytics teams to stay current on best practices and new model techniques
Communicate value of analytics to Fab leadership and business partners and increase the awareness of analytics Fabs
Facilitate generating and maximizing value from analytics solutions

Requirements

Bachelor’s degree in quantitative fields such as Statistics, Mathematics, Computer Science, Operation Research, Engineering, Physics, Chemistry, Biostatistics, Economics, Data Science, or a related Engineering degree
A minimum of 4 Years of experience in analytics space with proven track record of innovation as a forerunner
Experience with key data science techniques, including forecasting, recommendation systems, logistics optimization, churn and segmentation analysis, and deep learning
Proficiency in R, Python, SAS, SPSS, or STATA, with strong data visualization capabilities
Experience building and scaling optimization and cloud‑based solutions, including productionizing recommendation engines
Ability to implement business‑focused advanced analytics that address industry‑specific challenges
Strong communication skills and proven leadership in guiding cross‑functional teams
Demonstrated product mindset with experience working in Agile environments
Ability to build trust with stakeholders and work effectively in ambiguous, unstructured problem spaces