About AbbVie

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

The Associate Data Scientist I is a technical expert that will work with clinical, research, or commercial data to help address critical business needs by analyzing data, using statistical models and applying machine learning to generate insights, make predictions, and derive actionable recommendations.  A continuous drive to improve existing methods and processes is essential. Demonstrate proficiency in a broad range of techniques and methods for data and health sciences, including software development, data warehousing, statistics, and/or machine learning.

Responsibilities:

• Analyze complex datasets to generate insights, make predictions, and solve business problems.
• Use statistical models, machine learning, and advanced analytics to influence leadership decisions.
• Understand the broad objectives of the project and your role in achieving those objectives; modify approach when required.
• Effectively organize and present project objectives and progress.
• Understand and adhere to corporate standards regarding applicable Corporate and Divisional Policies, including code of conduct, safety, GxP compliance, and data security.

Required Qualifications:

• Bachelor’s degree in computer science, data science or relevant field.
• Programming skills in Python, R, or SQL.
• Prior exposure to data science or data analytics.
• Ability to multitask and work within timelines.
• Demonstrated ability to learn, understand and master new technologies.

Preferred Qualifications:

• Knowledge of popular libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch.
• Experience with Tableau and Power BI visualization tools.
• Hands-on experience using large language models and machine learning algorithms.
• Demonstrated experience applying AI/ML in clinical or pharmaceutical contexts.

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​

• The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at  the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors  including  geographic location, and we may ultimately  pay more or less than the posted range. This range may be  modified in the future. ​

• We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.​

• This job is eligible to  participate in our short-term incentive programs. ​

Note: No amount of pay is  considered to be wages or compensation until such amount is earned,  vested,  and determinable. The amount and availability of  any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a   particular employee  remains in the Company's sole and absolute discretion unless and until paid and may be  modified at the Company’s sole and absolute discretion,  consistent with applicable law. ​

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.  Equal Opportunity Employer/Veterans/Disabled. 

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html