Otsuka is looking for a technically strong data scientist in the Medical and Real World Data Analytics (MRWDA) organization to convert diverse types of clinical and non-clinical data to evidence for demonstrating health outcomes through the use of Machine Learning (ML) and Artificial Intelligence (AI). The primary role of this position is to work with data scientists, statisticians, data programmers, and other stakeholders to convert data into evidence, decisions, and to demonstrate value of therapeutic solutions in the Real World. The position will be responsible for applying existing methodologies as well as developing new methodologies and algorithms, where appropriate, to solve problems end-to-end from conception to final delivery. To achieve this, the position will collaborate within the team and stakeholders, but will be accountable for all aspects related to methodologies and data analyses.
The prospective candidate must have an excellent knowledge of advanced methods, including Deep Learning, and demonstrated experience in applying those to novel problems involving diverse types of real-world data. Such data could include text/documents, images, videos, speech, sensor data, time-series or longitudinal data, surveys, structured data, and clinical data. The successful candidate will be enthusiastic to grow in new directions and solve new problems in a Pharmaceutical setting.
Fresh candidates with advanced degrees and demonstrated experience are welcome to apply.
Establish and implement end-to-end proof of concept for data analyses across functional areas
Build rapid prototypes for data analyses, Machine Learning (ML) /Artificial Intelligence pipelines systems in collaboration with data scientists and data programmers
Develop new data driven and digital models to transform business operations
Develop and maintain ML/AI models on diverse data
Lead data science aspect of projects end-to-end from conception to Proof-Of-Concept to delivery
Establish strong collaborations with stakeholders as Global Medical Affairs, Value and Real World Evidence, Market Access or other stakeholders to understand data and advanced analytics needs and translate them to data science initiatives. Provide support to data and infrastructure initiatives as needed. Work closely with data scientists, statisticians, and stakeholders including Medical Affairs, Value and Real World Evidence, and Market Access to support data products, insights, and evidence
Work closely with Data Technologies and Clinical Analytics team members to understand data and leverage data technologies
Ensure delivery of quality and on-time results by vendors and their resources, when applicable
Develop end-to-end data analyses, including efficient manipulation of large databases including complex data processing, filtering and manipulating data from multiple sources
Lead development and implementation of efficient, modular, reusable ML/AI models and data pipelines in modern computational environments to process variety of Real World data
Define appropriate datasets by identifying patient subpopulations or disease cohorts, pooling data across datasets to enable rapid exploratory analyses, experimentation, and/or well-defined analyses. Identify data gaps and to recommend new avenues for collecting data
Ensure professional development to enhance knowledge, skills, communication, scientific and technical methodologies, operational efficiency and compliance with policies and regulations
Collaborate with stakeholders to define and deliver on analyses requests with accountability for timely and high-quality delivery
Provides data science/ML/AI consultation within the team and to stakeholders for ad hoc analysis requests including methodologies to answer relevant questions
Presenting to senior leadership as well external audience
Serve as the key point of contact for Data or Data Analysis requests for Data Science projects or requests
Participate in defining and lead AI/ML/Data Science initiatives
Master's Degree required and PhD strongly preferred in Computer Science, Engineering, Physics, Statistics, or a related field with focus on ML/AI.
3 - 5 years hands on experience in advanced machine learning or data sciences. Candidates with a recent PhD or a postdoc are welcome to apply
Command of principles of machine learning, statistical analysis, data mining algorithms, and mathematical modeling
Demonstrated ability to use knowledge of recent techniques and develop new methodologies. Expertise in multiple areas of Machine learning, both classical and modern deep architectures
Demonstrated experience in applying Machine Learning to at least one of the areas: Computer Vision, NLP/text analytics, social network analysis, bioinformatics, sensor data, web applications, health sciences, digital health, claims data, disease registries, mechanism design, etc.
Deep expertise and hands on experience working with large complex datasets along with an expert understanding of data storage, data structures, and modern databases (NoSql, Graphs).
Proficiency in programming with excellent development and data analyses skills using state-of-the-art technologies and languages (python, R, Matlab, SAS, C++, or other scripting languages)
Expertise with key machine learning packages (pytorch, TensorFlow, Keras, ML packages in AWS or GCP) to rapidly develop prototypes
Expertise in organizing, retrieving, searching, processing, mapping, manipulating data in ML/AI pipelines. Ability to process and analyze diverse data, including text/documents, images, videos, speech, sensor data, time-series or longitudinal data, surveys, structured data, and clinical data
Awareness and understanding of data privacy, anonymization, data protection, security, data ethics and how to address these in data analyses
Hands on technical and project leadership with full accountability and team spirit
Strong Acumen to translate business problems into data science problems, solve them, and present as an end-to-end solution
Strategic and outcomes-oriented mindset that balances depth, breadth to demonstrate value
Strong technical writing, editing, and communication skills along with collaborative mindset
Excellent organizational skills with an ability to embrace change and effectively manage multiple projects and consistently plan work to meet deadlines
Finally, a desire backed by will and commitment to make a positive difference to human health
Experience with data from clinical, observational and other Real World studies, claims data
Experience in working with cloud environments (e.g., AWS or GCP) and Big Data technologies
Experience in machine learning on large size data using MapReduce and Hadoop preferred
Experience in health care or commercial data analytics strongly preferred
Demonstrated ability to synthesize information to develop recommendations, and influence organization on a recommended path.
Experience with information extraction and retrieval or demonstrated ability to develop skills rapidly
Experience with latest technologies
Disclaimer: This job description is intended to describe the general nature and level of the work being performed by the people assigned to this position. It is not intended to include every job duty and responsibility specific to the position. Otsuka reserves the right to amend and change responsibilities to meet business and organizational needs as necessary.Otsuka is an equal opportunity employer. All qualified applicants are encouraged to apply and will receive consideration for employment without regard to their protected veteran or disabled status, or any protected status.
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