Data Scientist

Company Description

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.

Responsibilities

• Consult with business users in the analysis of requirements and recommend solutions which anticipate the future impact of changing business needs.
• Develop advanced data analytical models and techniques from supervised and unsupervised machine learning, statistical analysis, deep learning, predictive modeling, and Gen AI.
• Build relationships with stakeholders and collaborate with other statistical and data science teams in AbbVie while mentoring and coaching team members.
• Ensure that data presented to key stakeholders and presentations maintain study integrity.
• Support multiple use cases and ensure that each work product is fit for purpose.
• Participate in functional innovation and process improvement initiatives when assigned.
• Ensure adherence to federal regulations and applicable local regulations, Good Manufacturing Practices (GMPs), ICH Guidelines, AbbVie Standard Operating Procedures (SOPs), and functional quality standards.
• Stay abreast of new and/or evolving local regulations, guidelines and policies related to clinical development.
• Coach and mentor junior team members.
• Identify business needs and support the creation of standard KPIs, reports, and statistical analyses.

Qualifications

• Bachelor’s or Master's degree in statistics, mathematics, analytics, bioinformatics, data science or equivalent field with 4+ years (BS), 2+ years (MS) or 0+ years (PhD) of related experience.

Skills

• Intermediate-level proficiency in R, Python or other statistical packages.
• Intermediate-level knowledge of statistical and data mining techniques.
• Intermediate proficiency with visualization tools like PowerBI, Spotfire, Tableau or equivalent.
• Intermediate proficiency with data science platforms like Dataiku, Snowflake, Databricks.
• Experience with Machine Learning and other advanced analytics techniques preferred.
• Demonstrated effective communication skills.
• Demonstrated ability to communicate analytical and technical concepts in layman’s terms.
• Demonstrated problem-solving and analytical skills.
• Demonstrated history of successful execution in a fast-paced environment and in managing multiple priorities effectively.

Benefits

• Paid time off (vacation, holidays, sick