Data Scientist

Kyowa Kirin is a fast-growing global specialty pharmaceutical company that applies state-of-the-art biotechnologies to discover and deliver novel medicines in four disease areas: bone and mineral; intractable hematologic; hematology oncology; and rare disease. A Japan-based company, our goal is to translate science into smiles by delivering therapies where no adequate treatments currently exist, working from drug discovery to product development and commercialization.

In North America, we are headquartered in Princeton, NJ, with offices in California, North Carolina, and Mississauga, Ontario.

Summary of Job: The Data Scientist will be responsible for applying advanced analytics and creating data-based insights for the Oncology, Rare Disease, and CNS business franchises in Kyowa Kirin North America. This role will report to the Senior Director, Business Insights and Analytics, and will be responsible for advancing data science and advanced analytics capabilities by leveraging best practices in data science, data mining, and advanced statistical modeling to drive a culture of data-driven decision-making.

This role requires a unique combination of skillsets and strong business acumen along with the technical competence to gain the trust of internal stakeholders and to develop innovative solutions that address critical business needs.

• Play a key role in identifying opportunities for machine learning and business intelligence to solve unmet medical needs and support the analysis of data to generate market insights.
• Create artificial intelligence (AI)/ machine learning (ML) in fracture to support key strategic initiatives.
• Implement advanced analytics in support of our commercial teams, including explorative applications of machine learning, deep learning, and artificial intelligence.
• Influence critical strategic business decisions by enhancing intelligence systems and predictive analytical techniques to address current and future business objectives.
• Leverage advanced data integration and governance capabilities through cloud computing, and AI/ML.
• Utilize machine learning to build predictive models for application in commercial initiatives.
• Develop automated capabilities that enable the application of machine learning across the Company’s portfolio of medicines.
• Ability to build and fine-tune algorithms that scale up from small-scale proof-of-concept stage to full production systems in a timely manner.
• Communicate complex findings and insights to bother technical and non-technical stakeholders through data visualizations, reports, and presentations

• A Bachelor’s degree in Statistics, Computer Science, Economics, applied mathematics, or a related field is required. A master’s or Ph.D. degree is preferred.

• At least 10 years of relevant experience, including data science, advanced statistics, and business analysis.
• Strong understanding of healthcare data & and technology; cross-industry experience in pharmaceutical, consumer, or technology industries preferred.
• Strong quantitative and diverse analytical skills: exploratory data analyses, computer science, statistics, modeling, mathematics, programming languages, and business acumen.
• Extensive experience working with large complex data and proficiency in corresponding query/ programming languages such as SAS, R, Python, or SQL plus experience with other big data technologies such as Hadoop.
• Querying, algorithms, data engineering, natural language processing, engine recommendation, experimentation, programming, data storytelling and intelligence, predictive modeling, and machine learning.
• Strong knowledge of secondary data sources including syndicated sales, promotional & and marketing data, longitudinal patient-level data, and diagnostic lab data; experience with payer data.
• Proficiency in manipulating and extracting insights from large longitudinal data sources, such as claims, diagnostic, EMR, and other data sets.
• Expertise in managing and analyzing a range of large, secondary transactional databases is required.
• Experience with field force analytics, including customer segmentation, targeting, and promotional…