Scientist in Natural Language Processing, Data Science & Digital Health (JRD)

Key Skills

Aartificial intelligence, AWS, Azure, Data science techniques, Google Cloud Platform (GCP), HuggingFace, Machine learning techniques, Natural Language Processing (NLP), Natural Language Toolkit - NLTK, PyTorch, Random forests, RNNs, spaCy, TensorFlow

Job Description

Job Title: Scientist in Natural Language Processing, Data Science & Digital Health (JRD) 

Janssen Research & Development, a Johnson & Johnson company, is recruiting for the role of Scientist in Natural Language Processing . The primary location for this role is flexible and includes Spring House, PA; Titusville, NJ; Raritan, NJ; La Jolla, CA; San Francisco, CA; Cambridge, MA; Beerse, Belgium; Leiden, the Netherlands; High Wycombe, the UK; Neuss, Germany; Zug, Switzerland. Remote work may be considered on a case-by-case basis and if approved by the Company.

Janssen Research & Development develops treatments that improve the health and well-being of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, neuroscience, and infectious diseases. Our goal is to help people live longer and healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about Janssen Research & Development, one of the Pharmaceutical Companies of Johnson & Johnson, please visit  https://www.janssen.com/.

The Data Science Analytics & Insights team within Janssen Research & Developments develops innovative solutions using a variety of data sources across multiple disease and therapeutic areas. We are looking for an outstanding candidate for the role of Scientist in Natural Language Processing whose responsibilities include:

Key Responsibilities:

• Conceive, develop, and validate NLP solutions to high-priority scientific problems.
• Shape internal and external collaborations and define the scope of research projects.
• Extract insights from complex, unstructured (bio-)medical texts and patient narratives to improve drug discovery and development.
• Participate in cross-functional collaborations with internal stakeholders and external partners.
• Clearly communicate the state-of-the-art methods and results to diverse audiences and partners to support decision-making.
• Publish findings in top-tier journals and conferences.

Qualifications

Required qualifications:

• A Ph.D. degree in NLP or a related discipline (e.g., computational linguistics, computational biology, computer science, artificial intelligence, machine learning, data science, applied mathematics, statistics, electrical engineering, signal processing).
• Minimum 2 years of relevant experience after PhD.
• Proven track of record in NLP, text mining, and machine learning backed by publications in top-tier journals and conferences.
• Experience with natural language inference, summarization, generation, name entity recognition, or sentiment analysis techniques.
• Experience with basic and advanced NLP techniques (e.g., RNNs, transformer neural networks, BERT, GPT) and development tools (TensorFlow or PyTorch, HuggingFace, spaCy or NLTK).
• Experience with advanced analytics techniques (e.g., random forest, SVM, boosting, neural networks).
• Proficiency in one or more programming languages such as Python, R, Scala, C++, Java. 
• Experience with software development tools (Git) and one of project tracking systems, such as Gitlab, Jira, Confluence, Asana.
• Analytical mindset and critical thinking.
• Ability to continuously learn and acquire new knowledge and skills.
• Ability to effectively communicate technical work to a wide and diverse audience.
• Passionate about leveraging data to drive scientific innovation.
• Can-do attitude and ability to work in a diverse, multi-disciplinary team.

Preferred (“nice-to-have”) qualifications:

• Experience with analyzing electronic health records and other types of free text data.
• Experience with working closely with healthcare professionals.
• Familiarity with drug discovery, drug safety, and clinical development processes.
• Expertise in one or multiple healthcare or pharmaceutical industry functions and disease areas (e.g., mental health).
• Strong knowledge of statistics.
• Experience with cloud platforms (e.g., AWS, GCP, Azure). 
• Experience working within a start-up, technology, or healthcare industry.