Senior Data Scientist - APAC

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Data & Analytics in the Asia Pacific is a new Veeva venture with the aim of using Advanced Analytics and Machine Learning to help Life Sciences improve healthcare engagement and patient outcomes. If you are excited about building a new offering in a start-up environment, developing, and scaling analytics solutions, and working with a diverse, international group of expert colleagues, then this role could be right for you.

The Senior Data Scientist is responsible for defining and executing the Data Science agenda of the team. You will design and lead the execution of analytics projects for various pharma and healthcare stakeholders. This will involve working with these stakeholders to understand their business and operational challenges, developing the appropriate analytical techniques, then building and implementing models for real-world impact.

You will also play a role in helping the business make decisions about the right analytics architecture and pipeline underpinning our operations. This will ensure the efficiency and scalability of what we do.

What You'll Do

• Work with a variety of pharma commercial and healthcare datasets in Asia.
• Work in a project environment – supporting the needs of healthcare stakeholders through data science.
• Design the appropriate ML and Statistics techniques required to support priority healthcare use cases.
• Lead and execute the end-to-end advanced analytics and data science components of our projects.
• Build an efficient and scalable analytics pipeline to support replication of our analyses.

Requirements

• 5+ years in data science roles.
• Experience building commercial analytical solutions in pharma, healthcare, or consumer goods.
• Highly proficient in Python and SQL.
• Highly proficient in Machine Learning across a variety of methods both supervised/unsupervised.
• g., Clustering, classification, time series and forecasting, and recommendation engines.
• Experience executing analytics within cloud-native environments.
• Experience with the build, deploy, produce, and operate life cycles of machine learning pipelines.
• Strong written and oral communication skills with senior, business audiences.

Nice to Have

• Familiar with Agile and working in a Scrum Team.
• Experience in Real-World Evidence.
• Experience in consulting or customer-facing roles.
• Publications in peer-reviewed journals or conferences related to the field of AI.