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AbbVie hat es sich zur Aufgabe gemacht, innovative Arzneimittel zu entdecken und bereitzustellen, die schwerwiegenden Gesundheitsprobleme von heute bekämpfen und den gesundheitlichen Herausforderungen von morgen gewachsen sind. Unser Ziel ist es, das Leben der Menschen in verschiedenen wichtigen Therapiebereichen wie der Immunologie, der Onkologie, den Neurowissenschaften, der Augenheilkunde, der Virologie, der Frauengesundheit und der Gastroenterologie zu verbessern. Mit dem Portfolio von Allergan Aesthetics bieten wir darüber hinaus Produkte und Dienstleistungen im Bereich medizinische Ästhetik an. Für weitere Informationen über AbbVie besuchen Sie uns unter www.abbvie.com. Folgen Sie @abbvie auf Twitter, Facebook, Instagram, YouTube und LinkedIn.

Principal Marketing Analytics & Data Scientist

Standort Waukegan, Illinois Sekundär Irvine, Kalifornien; Florham Park, New Jersey Anzeigen-ID R00090356 Kategorie Marketing Bereich AbbVie

The Marketing Analytics and Business Insights (MABI) function supports AbbVie’s US organization and is comprised of highly respected researchers, analysts, data scientists and strategists who are committed to being best-in-class within the biopharmaceutical industry.  We serve as strategic in-house counsel, ensuring that all decisions leverage the key insights that we develop.  We continue to build new capabilities and skill sets, encouraging our team members to pull up a chair, be themselves, be creative, speak their minds, and do good work.  We are a passionate, diverse, flexible, and inclusive organization with a culture that supports the best ideas, wherever they originate.  We are smart, fun, quirky, and innovative – and we’d love for you to join us.

This role is part of an Analytics Center of Excellence housed within the MABI function that aims to differentiate AbbVie as a leader in omni-channel customer experiences and to build lasting relationships with consumers through omni-channel experiences powered by data and analytics.

The individual in this role will be a key contributor to the team responsible for omni-channel analytics supporting the growing roadmap of consumer capabilities.  This individual is skilled in designing and conducting analytics to optimize an integrated customer experience across channels.

Core Job Responsibilities:

·    Develop and implement methods for extracting patterns and correlations from both internal and external data sources using machine learning toolkits.

·    Construct and develop predictive models that are reliable, scalable, and modular.

·    Maintain and optimize existing machine learning models.

·    Develop plan to put machine learning models into production.

·    Adopt new tools/techniques to increase performance, automation, and scalability.

·    Report, visualize and communicate results to internal stakeholders on a regular basis.

·    Work with stakeholders to define business questions, requirements, timelines, objectives, and success criteria.

·    Examine relevant data and quickly develop an analytics plan that will answer key business questions and create value for clients.

·    Work with data sets of varying degrees of size and complexity, including both structured and unstructured data.

·    Transform data into actionable insights and recommendations. Present clear and concise results. This includes processing, cleansing, and verifying the integrity of data used for analysis.

·    Develop analytical solutions by using and applying appropriate methodology – including, but not limited to, regression, forecasting, clustering, decision trees, simulation, optimization, machine learning, and neural networks.

·    Design and define approach to scale and operationalize models for machine learning.

·    An experience in measurement solutions like lift measurement, Multi-Touch Attribution etc.

We primarily recruiting for candidates in Chicago IL, Irvine CA or Florham Park NJ. Relocation is needed for candidates not currently residing in noted cities (IL, CA, NJ).  


Qualifications

·Masters’ degree required in quantitative fields such as Statistics, Engineering, Operations Research, Computer Science or Economics.

·7+ years’ progressive business experience in marketing analytics, database marketing, data engineering and predictive modeling or strong academic background.

·Ability to develop advanced machine learning models using scikit-learn, Keras, or other machine learning frameworks.

·Strong algorithmic design skills. Execute analytical experiments methodically while outputting reproducible research.

·Demonstrated proficiency in Python, R, SQL, Relational databases (Teradata, Oracle etc.), BI tools (Power BI, Qlik Sense) and IDEs like Jupyter, with experience in leveraging available packages and libraries to accelerate time to market.

·Experience with big data technologies like Hive, Impala, Hue etc.

·Experience in Pharmaceutical datasets like patient claims and syndicated data from IQVIA (IMS) and Symphony Health Solutions a big plus.

·Strong problem solving and interpersonal skills and ability to work as part of a diverse team including IT and Line of business analytics teams.

·Bring a strong entrepreneurial spirit and ability to think dynamically.

·Strong communication skills, written and verbal.

·Project management experience; solid attention to detail and operational focus.


AbbVie is committed to operating with integrity, driving innovation, transforming lives, serving our community, and embracing diversity and inclusion. It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because 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, status as a protected veteran, or any other legally protected group status.


Wesentliche Arbeitstätigkeiten: Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)

Dienstreisen: No

Jobtyp: Experienced

Arbeitszeitmodell: Full-time

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