Key Responsibilities:
Project Execution: as individual contributor, responsible for
Building and exhibiting deep expertise on available data sets and supports data enabled decision making using data from external suppliers (JDI, JPM, DDD, etc.) in Japan and internal data for various other sources
Ensuring high stakeholder satisfaction through consistent delivery of high quality, timely and insightful outputs throughout analytics value chain on various objectives related to
Brand descriptive analytics and visualization to provide data-based insights on planning, measurement and segmentation e.g. brand performance, market monitoring, new brand launches, customer analysis
Market intelligence reporting on KPIs related to sales, sales growth, wholesaler inventory, market share, market growth, sales force activity, P2P and non-personal channel promotional impressions and engagement metrics etc.
Data support through data mining and warehousing
RWD engineering and analytics
build comprehensive understanding of Japan RWD datasets (MDV/JMDC), create and maintain optimal data pipeline architecture ETL/ ELT into structured data
Build analytics tools that utilize the data pipeline to provide actionable insight into patient behaviour and treatment journey
Developing into a trusted advisor by actively participating in various phases of the project including kick-off, methodology development, execution, insight generation and data visualization and results presentation to various stakeholders
Participating in meetings with stakeholders and communicating the final outputs and recommendations.
Project Delivery: as team member, supporting the team lead in driving
quality, speed, value and compliance throughout the analytics value chain
project management for seamless project execution, prioritization and high-quality delivery
creation and maintenance of standard operating procedures (SOPs), quality checklists that will enable excellent quality outputs
shared learning forums to identify challenges and establish best practices
expansion of analytical capability of the team by taking on more complex projects and delivering value
process improvements and implementation of analytical best practices
Education:
Degree in sciences or quantitative discipline i.e. Finance, Econometrics, Statistics, Engineering or Computer Sciences. Experience in pharma/healthcare industry is preferable.
Experience:
4-6 years of analytics experience with demonstrated ability to think strategically in an ambiguous environment in analytics
Experience in pharma industry is preferable
Experience building and optimizing big data data pipelines , architectures and data sets
Technical Skills
Strong experience in SQL
Strong experience in data visualization tools e.g. Tableau/PowerBI
Experience in R, Python, Knime (at least 1)
Excel, VBA (added advantage)
Strong knowledge of various pharma databases (high preference for Japan dataset and landscape knowledge including JDI, JPM, DDD, Ultmarc, M3/NMO/MedPeer/Carenet etc.)
Advanced MS-office skills (MS-Excel and MS-PowerPoint)
Experience with relational SQL databases, especially AWS Redshift.
Experience with AWS cloud services Preferable: S3, EC2, Lambda, Glue, EMR, RDS, Pyspark highly, preferred. Experience with similar services on another platform would also be considered.
Analytical Skills
Strong experience in business analytics including insight generation for commercial leadership.
Experience in data manipulation, cleaning and preparation (database querying, descriptive statistics)
Problem solving skills and lateral thinking ability
An eye for detail
Soft Skills
Strong work ethic and personal motivation
Good presentation skills
Experience in working with business partners located in another country, especially non-English speaking country like Japan
Interpersonal and communication skills with ability to work across time zones
Ability to operate effectively in an international matrix environment
Strong stakeholder management skills
Strong team player who is dynamic and result-oriented
