Manager - Data Science
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.
AbbVie Operations Business Insights (OBI) is working to transform AbbVie operations organization to enable the use of data and analytics to drive world-class innovation, performance, and agility.
Abbvie’s OBI group is looking for Manager, Data Science responsible to define, manage and build a scalable Business intelligence and Data Science platform and solutions that will enable business process metrics and advanced analytics for Operations. The individual will be in involved in actively managing and contributing to a high performing team of data scientists and engineers who are building the foundational pillars of advanced machine learning solutions to solve some of the most relevant business problems. The candidates strong data science background should include innovation in a robust experimentation framework that enables simultaneous testing of multiple levers – timing, cadence, verbiage, channel etc. building core elements of NLP framework that enables real time intelligent conversations with business; recommendation engine that helps determine the next best action etc.
The role reports to the Director, Operations Business Insights (OBI) and works closely with all business and IT leadership. Our environment is fast-paced and requires a candidate who is flexible, detail-oriented, thrives on ambiguity and can drive results across cross-functional groups.
- Leadership and People Responsibilities: Oversee the hiring and training of new and existing staff, conduct performance reviews and provide leadership, technical guidance and coaching to staff. Build organizational talent by creating a learning environment that ensures employees realize their highest potential
- Develop strategies to leverage enterprise data and build through the delivery of easy to use reports and dashboards, sophisticated data analysis and advanced data modelling.
- Develop and maintain a demand roadmap aligned with priority, IT capacity, technical dependencies, and ongoing project portfolio.
- Manage portfolio of business intelligence and Data Science projects to ensure on-time delivery
- Design, build and optimize data visualizations tools to provide actionable insights that enhance business decision making
- Finance/Budgetary Responsibilities: Manage the budget - monitor and control resources, expenses, and capital costs against the budget.
- Provide expertise in modeling & statistical approaches (machine learning methods ranging from regression methods, decision trees, deep learning, NLP techniques, uplift modeling; statistical modeling such as multivariate techniques etc.) and leverage the right technique suited for the problem .
- Manage deliverables across multiple projects with a bias to action, help set right expectations on LOE & timelines.
- Collaboration – with Operations cross functional team and business stakeholders in implementing scalable models in cloud platforms and present technical findings in a variety of formats (reports, PPT, graphs, figures and tables), formulating recommendations, and effectively presenting the results to non-technical audiences.
- Champion utilization of business intelligence technology across IT organizations and business functions. Lead and develop an enterprise approach to operational analytics, data visualization, analysis, and modelling.
- Regulatory Compliance Responsibilities: Protect our brand and reputation by safeguarding our assets and maintaining compliance with all governing policies. Assure all relevant internal financial, data privacy and security policies are met
- Enhance Software Development Lifecycle (SDLC) documentation to align with agile methodologies and deliver high-quality reporting solutions quickly and continuously
- Benchmark and evaluate business intelligence best practices and solutions related data visualization and data mining that will be sustainable and fit our AbbVie environment
- Bachelor’s Degree with 7+ years, or Master’s with 4+ years or PhD with 2+ years professional experience in any of the following fields: Computer Science, Data Science, Applied Math, Engineering, Operation Research, Statistics, Epidemiology, or other related quantitative fields. Professional Experience includes the following areas:
- Hands-on experience designing and implementing end-to-end solutions using Machine Learning in a fast-paced environment
- Expert level proficiency with common modeling tools and frameworks, e.g. Python, R, Scala, etc.
- Solid understanding of key BI trends and emerging technologies such as Hadoop, NoSQL, Modern Data Warehouse.
- Experience managing large and complex BI projects across multiple business functions.
- Experience reviewing and streamlining business processes, including gathering and documenting business requirements, developing, and implementing new processes and procedures. Solid experience on Software Development Lifecycle (SDLC) methodologies
- Ability to communicate problems in terms that are understandable to end users at all levels
- Strong analytical and problem resolution skills
- Knowledge of Pharmaceutical industry & validation environment
- Demonstrated ability to coordinate cross-functional teams towards task completion
Significant Work Activities
Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)
Yes, 10 % of the Time
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.