Senior Data Scientist

Technical Skills

• Strong proficiency in Python and SQL.
• Hands-on experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Experience building predictive, classification, forecasting, recommendation, or optimization models.
• Strong knowledge of statistics, experimentation, predictive modeling, and model evaluation techniques.
• Experience working with large-scale data platforms and cloud-based environments.
• Familiarity with MLOps, model deployment, model monitoring, and production AI practices.
• Experience using modern software development and version control practices.
• Business & Leadership Skills
• Strong analytical and problem-solving capabilities.
• Excellent communication and stakeholder management skills.
• Ability to translate business challenges into data-driven solutions.
• Demonstrated ability to work independently while collaborating effectively across teams.
• Strong organizational and project management skills.
• Passion for innovation, continuous learning, and practical application of AI technologies.

Preferred Qualifications

• Experience working with healthcare, pharmaceutical, claims, payer, patient support, or market access data.
• Experience developing AI-powered decision support systems.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with Snowflake, Databricks, Spark, or other large-scale data environments.
• Experience deploying Generative AI or Large Language Model solutions.
• Experience operating in regulated industries where data quality, governance, and validation are critical.
• Experience rapid-prototyping or evaluating generative-AI solutions is preferred.
• Experience with experimentation or causal measurement methods is preferred.
• 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 long-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

About AbbVie

Qualifications

• Bachelor's degree in Statistics, Computer Science, Data Science, Mathematics, Engineering, Economics, Operations Research, or a related quantitative discipline.
• Advanced degree (Master's or PhD) is preferred but not required.
• Equivalent combinations of education, specialized training, and relevant professional experience will be considered.
• 6+ years of experience developing and deploying machine learning, artificial intelligence, or advanced analytics solutions in production environments.
• Demonstrated experience delivering production data science solutions and evaluating their performance against business outcomes.
• Strong proficiency in Python and SQL.
• Hands-on experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Experience building predictive, classification, forecasting, recommendation, or optimization models.
• Strong knowledge of statistics, experimentation, predictive modeling, and model evaluation techniques.
• Experience working with large-scale data platforms and cloud-based environments.
• Familiarity with MLOps, model deployment, model monitoring, and production AI practices.
• Experience using modern software development and version control practices.
• Strong analytical and problem-solving capabilities.
• Excellent communication and stakeholder management skills.
• Ability to translate business challenges into data-driven solutions.
• Demonstrated ability to work independently while collaborating effectively across teams.
• Strong organizational and project management skills.
• Passion for innovation, continuous learning, and practical application of AI technologies.
• Experience working with healthcare, pharmaceutical, claims, payer, patient support, or market access data.
• Experience developing AI-powered decision support systems.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with Snowflake, Databricks, Spark, or other large-scale data environments.
• Experience deploying Generative AI or Large Language Model solutions.
• Experience operating in regulated industries where data quality, governance, and validation are critical.
• Experience rapid-prototyping or evaluating generative-AI solutions is preferred.
• Experience with experimentation or causal measurement methods is preferred.