Pfizer Head, A.I. Data Sciences in Groton, Connecticut
Data in pharmaceutical research has constantly increased in both volume and complexity and its correct interpretation in a biomedical context has become more and more dependent on advanced analytical and data management skills.
As the Head of AI for Data Sciences, you will be responsible for helping to accelerate drug discovery by enhancing our decision-making process, working with a wide range of roles to extract actionable insights from complex data sets.
Acts as the key scientific and technical Artificial Intelligence expert for Data Monitoring and Management; defines and drives the data monitoring and management strategy and standards in the AI space, utilizing techniques such as RPA, Natural Language Processing, Machine Learning, etc., across all areas of Data Monitoring and Management (DMM) (including data management, Risk-Based Monitoring, and standards). Operationally manages the application and utilization of AI technologies and practices within DMM organization.
Represents DMM and supports AI and innovation related interactions with external vendors , BT, COE, senior leaders, and representatives across GBDM. Actively coordinates resources to ensure successful AI project implementation outcomes.
Defines and effectively communicates to DMM colleagues and partner organizations AI project requirements and partners with BTQA to follow all appropriate standards for compliance.
Partners with colleagues to ensure alignment of data quality across DMM, preferred partners, Development China and Development Japan.
Proactively identifies issues, successfully leading initiatives which result in continuous improvement and quality deliverables across DMM.
Defining and driving the AI strategy to create a roadmap detailing the short and long term implementation for DMM, including techniques from RPA (robotic process automation) ML (machine learning), NLP (natural language processing), etc.
Bachelor's degree in a field such as Statistics, Mathematics, Statistics, Economics, Physics, Engineering is required. A Masters Degree Preferred.
10+ years of experience in the IT industry preferred
3+ years of experience with Machine Learning and Artificial Intelligence techniques and tools
5+ years of experience with data sources and platforms
At least 5 years in a leadership role.
Flexibility, problem-solving and leadership skills, genuine intellectual curiosity, borderless ideation and eagerness to contribute are key elements of the position.
Excellent communication skills to ensure alignment between computational and life scientists, Business Technologists, and physicians, as well as management.
A confident leader and subject matter expert, to drive innovation.
The individual should have demonstrable experience and passion for mathematics, statistics, signal processing, image analysis, machine learning, data mining, and data visualization.
Deep knowledge of scripting and analytics software, including R, Python, Pipeline Pilot, KNIME or equivalent.
Excellent theoretical understanding and real hands-on experience with deep learning and a range of more classical supervised and unsupervised machine learning methods, including but not limited to ensemble learning techniques (e.g. boosting, Random Forests) kernel methods (e.g. SVM), (non-linear) dimensionality reduction and feature selection methods are required. Practical knowledge of Bayesian methods and Natural Language Processing is a plus.
Demonstrable expertise with various machine learning packages, including deep learning toolkits (e.g. TensorFlow, mxNet, Theano or others).
Fluent in big data management tools, such as Hadoop, NoSQL data stores as well more traditional relational database
Demonstrated ability in the application of Machine Learning/AI in real-world settings with large scale data
Good understanding of the Drug Development is preferred.
Reports to Member of DMM LT, formulating strategies, standards and processes to be implemented across portfolio, ensuring compliance with global regulatory requirements
Partners closely with Clinical Data Scientist (CDS), Central Monitor (CM), Statistical Programming, Quality and other CD&O groups
Supports Teams across the Research/Business Units (R/BU), PEH
EEO & Employment Eligibility
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