Data Scientist

**About GlobalFoundries**

**Why GF**

Your work will have a direct impact on our expanding Fab Operations, in building out our platforms of purpose-built technologies such as smart mobile devices, personal computing, home and industrial IoT, automotive and more. You will have access to the latest technological developments at GF Labs, with opportunities for patent submissions, presenting your ideas on a global platform, and enjoy GF-wide collaboration across our fabs and offices around the world.

**Introduction**

As a Data Scientist, you will be reporting to Lead 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 the Lead Data Scientist in fostering partnership with Artificial Intelligence (AI) vendors/start-ups, support 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.

Required Qualifications:

- 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 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.

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.