Data Scientist Pipeline

at  Abbott Laboratories

HAVE YOU EVER WANTED TO MAKE A DIFFERENCE?

At Abbott, you will play a crucial role to help people live more fully at all stages of their lives. Abbott is a global healthcare leader and our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritional products and branded generic medicines. Our 113,000 colleagues have a daily impact on the life of people in more than 160 countries.

EDUCATION & EXPERIENCE

• Bachelor’s Degree in a quantitative field (i.e. Mathematics, Data Science, Statistics, Applied Statistics, Biostatistics etc.) preferred. Will consider relevant industry experience.
• Ability to develop custom sampling plans and sample size calculations for production and validation activities.
• Proficient in JMP / SAS statistical software (statistical analysis and programming) preferred but not essential. Training will be provided.
• Experience with relational databases (for example: Oracle Databases, MySQL, Microsoft Access, etc.) is desirable.
• An understanding of probability, statistical process control, hypothesis testing, non-parametric statistics, time series analysis, linear and logistic regression etc.

• Provide real time data analysis support to manufacturing in terms of process adjustments, material performance, investigations, programming and yield analysis.
• Ability to independently data mine multiple large, complex data sets to answer specific research / investigation questions. Curiosity to dig deeper and access other documentation sources to understand the data.
• The ability to strategically interpret statistical findings into a business significant context.
• Develop and lead projects focused on enhancing statistical methodologies. This includes providing input to the site data strategy and ensure delivery of the strategy
• Provides consulting on data analysis and statistical tools in support of trend analysis, root cause analysis, failure investigation, risk assessment, data management and data visualization to junior analysts and engineers.
• Develop automated solutions that address specific analytical objectives and facilitate report generation and distribution of analyses.
• Highly effective in presenting and communicating statistical results to lay audiences is required.
• Liaise with key business stakeholders; QA, Manufacturing, Engineering, R&D, Regulatory Affairs and Purchasing to ensure timely completion of activities.