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Job Description
Title:Data Scientist
About GlobalFoundries
GlobalFoundries is a leading full-service semiconductor foundry providing a unique combination of design, development, and fabrication services to some of the world’s most inspired technology companies. With a global manufacturing footprint spanning three continents, GlobalFoundries makes possible the technologies and systems that transform industries and give customers the power to shape their markets. For more information, visit www.gf.com.
Introduction
As a Data Scientist, you will be reporting to Sr Data Scientist and support in a pivotal role within the Data Science team and assist in the provision analytics technical requirements. You will support your manager to initiate the best-practices in analytics use case development/deployment/ scaling/maintaining the data science projects. You will assist your Lead Data Scientist in fostering partnership with Artificial Intelligence (AI) vendors/start-ups. You will support the Lead Data Scientist in developing and deploying machine learning or other statistical models to address the most complex and operational challenges. You will support in building scalable data products that will drive value and collaborate with all stakeholders across GlobalFoundries.
Your Job
- 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.
- Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements, and programs.
- Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, Operation Research, Engineering, Physics, Chemistry, Biostatistics, Economics, Data Science, or a related Engineering degree.
- A minimum of 5 Years of experience in analytics space with proven track record of innovation as a forerunner.
- Experience with the following types of data science techniques: Forecasting, Recommendation Systems, Logistics Optimization, Churn Analysis, Segmentation Analysis, Deep Learning
- Experience in creating business models in environments such as R, Python, SAS, SPSS, or STATA (Data visualization experience is a big plus)
- Experience in optimization and cloud environments to lead an inter-disciplinary team through scaling and productionisation of recommendation engines.
- Experience in implementing business-focused advanced analysis that can capture industry-specific nuances.
- Strong communication skills to interact with both technical and non-technical audience.
- Proven leadership skills to coach and guide team members to ensure on-time excellence.
- Product mindset with significant experience working in Agile teams.
- Ability to build a sense of trust and rapport within the team and senior leadership.
- Flexibility and ability to work with ambiguous problems and unstructured data.
- Strong bias towards action and proven ability toward iteratively and quickly to show incremental impact and value.
- Masters in data science or a related field
GlobalFoundries is an equal opportunity employer, cultivating a diverse and inclusive workforce. We believe having a multicultural workplace enhances productivity, efficiency and innovation whilst our employees feel truly respected, valued and heard.
As an affirmative employer, all qualified applicants are considered for employment regardless of age, ethnicity, marital status, citizenship, race, religion, political affiliation, gender, sexual orientation and medical and/or physical abilities.
All offers of employment with GlobalFoundries are conditioned upon the successful completion of background checks, medical screenings as applicable and subject to the respective local laws and regulations.
Information about our benefits you can find here: https://gf.com/about-us/careers/opportunities-asia
Skills
Artificial IntelligenceData VisualizationPythonData AnalysisData ScienceMachine LearningPrescriptive AnalyticsReportingSpssVisualizationData ScientistAnalyticsIf a job posting appears fraudulent, asks for payment, contains misleading information, or violates our guidelines, please report it immediately. Our team will review it promptly, Jobaaj does not charge any fee from the applicants.
About Company
GLOBALFOUNDRIES is the world's first full-service semiconductor foundry with a truly global manufacturing and technology footprint. Launched in March 2009 through a partnership between AMD [NYSE: AMD] and the Advanced Technology Investment Company (ATIC), GLOBALFOUNDRIES provides a unique combination of advanced technology, manufacturing excellence and global operations. With the integration of Chartered in January 2010, GLOBALFOUNDRIES significantly expanded its capacity and ability to provide best-in-class foundry services from mainstream to the leading edge. GLOBALFOUNDRIES is headquartered in Silicon Valley with manufacturing operations in Singapore, Dresden, and a new leading-edge fab under construction in Saratoga County, New York. These sites are supported by a global network of R&D, design enablement, and customer support in Singapore, China, Taiwan, Japan, the United States, Germany, and the United Kingdom.
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