Senior Data Scientist I
AbbVie’s mission is to discover and deliver innovative medicines 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: immunology, oncology, neuroscience, eye care, virology, women’s health and gastroenterology, in addition to products and services across its Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on Twitter, Facebook, Instagram, YouTube and LinkedIn.
The AbbVie Endocrinology Inc. (AEI) Strategy & Insights team is working to transform AEI into an agile data driven organization. This is a great opportunity to be a part of this team in leading the delivery of mid to large-scale, functional, and cross-functional advanced analytics initiatives designed to improve business efficiency & decision making. The Citizen Data Scientist will use a broad understanding of the access and reimbursement ecosystem paired with patient services information needs to lead data-driven initiatives across disciplines and subject areas for the team for ongoing & future projects. Additionally, this individual will be responsible for demonstrating both practical and innovative approaches while helping drive the reporting/analytics strategy for the AEI organization within Abbvie. The ideal candidate will be a proponent for innovation, best practices, sound design with data & information optimization in mind, strong development habits, and efficient team/project structures.
The Citizen Data Scientist will be responsible for driving advanced analytics and maturing AI at AEI, supporting multiple use cases across various business organizations in AEI; covering but not limited to language/image processing, machine learning analytics, deep learning analytics, etc. The use cases cover areas in access and reimbursement support, patient journeys, patient services, call center operations, commercial operations, patient assistance programs, and pharmacy services.
The successful Citizen Data Scientist will translate business needs into analytical questions; conduct data exploration leveraging data from integrated and disparate data sources across Abbvie (including data lakes, traditional relational and non-relational databases); develop model specification; design and perform analyses of operational, customer, and financial data; and translate these analytical findings into leading information for our business partners.
This position will act as an advisor to executive and management level decision makers. This individual will provide ‘end-to-end’ guidance on deployment of machine learning models including data governance and industry best practices with a lens towards agility and efficiency, leveraging a) data science and statistical methods, b) programming languages such as R, python, Spark, SAS, c) libraries such as TensorFlow, Pytorch etc. d) technology capabilities such as containers and orchestration (Docker, Kubernetes) in on-prem, cloud and hybrid infrastructures.
- Consult with internal and external stakeholders to determine how best to apply descriptive analysis and/or statistical learning to support business objectives across AEI’s use cases.
- Demonstrate a thorough understanding of concepts related to statistical methods, language and image processing and operations research and how to use them for solving real world problems.
- Apply linear models, machine learning algorithms, times series forecasting, and modern optimization methods (i.e. metaheuristics) to understand and/or predict events impacting various business operations.
- Understand the guidelines needed to build credible and efficient simulation models used to inform the decision-making process.
- Collaborate with subject matter experts and data engineers to deploy advanced analytic solutions into the operational environments.
- Adhere to agile project management frameworks and set the direction of data science initiatives.
- Adhere to applicable regulatory standards when executing initiatives considering privacy, compliance, and legal parameters.
- Master's degree or Bachelor's degree ( Preferred - applied math, computer science, data science, economics, informatics, statistics, etc.)
- Lifesciences, healthcare analytics background preferred.
- 6 years of combined experience navigating in both relational (Teradata, Oracle, etc.) and non-relational (Hadoop) database/data lake environments. 3+ years of experience in non-relational data environment required.
- 3+ years of practical experience with times series forecasting, Monte Carlo analysis, spatial analysis, and/or machine learning (random forest, neural nets, SVM, etc.)
- 3+ years of experience in operationalizing AI solutions from cloud providers such as AWS (ex. Sagemaker), Azure, GCP.
- 3+ years of experience working with R/Python; familiarity with libraries such as Tensorflow, café, Pytorch, etc.
- 2+ years of experience working with container-based machine learning models, automation, and operations.
- Strong SQL skillset is required.
- Experience with exploratory data analysis (EDA) and manipulating large data sets.
- Experience with accessing external data sources through various APIs (e.g. google distance matrix, quandl financial data, etc.)
- Familiarity with language models (SpaCy, NLTK, Stanford NLP) and using them to operationalize and enhance chatbot user experience is a bonus.
- Knowledge of Java/Scala/Apache Spark is a bonus.
- Knowledge of applicable regulations and standards affecting Pharmaceutical Products (e.g. CFR 210/211, cGMP) as well as knowledge of the applicable regulations affecting the practice of pharmacy (federal, state, and local as well as HIPAA) is a bonus.
Significant Work Activities
Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)
Job Level Code
Equal Employment Opportunity
At AbbVie, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients. As an equal opportunity employer we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.