Senior Data Scientist

at  Johnson Johnson

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com/ .
Excellent opportunity for a Senior Data Scientist to drive innovative data science solutions within J&J Innovative Medicine.
The Senior Data Scientist will design, develop, and lead the execution of impactful data science projects delivering insights and analytics to our business partners. Working within the Asia Pacific Data Science CoE and reporting to Associate Director, Data Science, you will use your deep technical expertise to advance the application of leading data science methodologies to domain-specific data assets to drive insights and decisions that improves the experience of health care professionals.

Responsibilities:

• Act as a hands-on, individual technical contributor to conceive, design, build, and implement state- of-the art machine learning solutions in collaboration with data scientists, IT partners and business partners across Asia Pacific.
• Leads data science projects by evaluating available and potential data sources, developing, and applying creative end-to-end scalable solutions that go beyond current tools to deliver insights for high-priority business challenges aligned with APAC priorities.
• Use AI/ML to transform our commercial strategy operations through impactful analytics projects that improve APSO strategic decisions.
• Effectively navigate technological, analytical, legal, and privacy complexities to achieve objectives.
• Remain at the forefront of the latest data science trends and best practices and contribute actively to internal J&J Data Science communities of practice to collectively improve enterprise data science knowledge and capability.
• Provide technical guidance to other team members as appropriate.

QUALIFICATIONS

• Master’s/PhD degree in a quantitative field such as computer science, computational biology, statistics, or a related discipline.
• At least 3-5 years of relevant hands-on data science experience in in developing and deploying ML solutions in a variety of ML areas such as recommendation engine, semantic search, forecasting, anomaly detection etc.
• Strong knowledge of foundational machine learning, and statistical modelling methods for supervised and unsupervised learning, including (but not limited to) regression analysis, clustering, outlier detection, decision trees, ensemble methods and boosting, and neural networks is required.
• Expert hands-on knowledge of Python and SQL programming.
• Experience with visualization software/tools is preferred.
• Experience working with good DevOps practices, familiarity with CI/CD tools and infrastructure as code (Docker/Kubernetes/etc.).
• Strong problem-solving skills with a solution-oriented mindset.
• Proven experience in prioritizing and leading a complicated portfolio of projects.
• Excellent communication, interpersonal, and written skills are required.

• Act as a hands-on, individual technical contributor to conceive, design, build, and implement state- of-the art machine learning solutions in collaboration with data scientists, IT partners and business partners across Asia Pacific.
• Leads data science projects by evaluating available and potential data sources, developing, and applying creative end-to-end scalable solutions that go beyond current tools to deliver insights for high-priority business challenges aligned with APAC priorities.
• Use AI/ML to transform our commercial strategy operations through impactful analytics projects that improve APSO strategic decisions.
• Effectively navigate technological, analytical, legal, and privacy complexities to achieve objectives.
• Remain at the forefront of the latest data science trends and best practices and contribute actively to internal J&J Data Science communities of practice to collectively improve enterprise data science knowledge and capability.
• Provide technical guidance to other team members as appropriate