Job Purpose:
The role of the Data Scientist will autonomously identify and pursue research with significant business impact, and make compelling cases for prioritization, resource allocation, and new product strategy Prioritize and execute in the face of
ambiguity, adapt tools to answer complicated questions and identify the trade-offs between speed and quality.
Key Accountabilities:
Analytics
- Develop analytics policy, standards, and guidelines.
- Establishes and manages analytics methods, techniques, and capabilities to enable the organization to Analyze data, generate insights, create value and
- Drive decision-making.
- Sets direction and leads the introduction and use of analytics to meet overall.
- Business requirements, ensuring consistency across all user groups.
- Identifies and establishes the veracity of external sources of information of relevance to the operational needs of the enterprise.
Methods and tool
- Provides advice, guidance, and expertise to promote the adoption of methods and tools and adherence to policies and standards.
- Evaluate and select appropriate methods and tools in line with agreed policies and standards. Contributes to organizational policies, standards, and guidelines for methods and tools.
- Implements methods and tools at program, project, and team levels including selection and tailoring in line with agreed standards.
- Manages reviews of the benefits and value of methods and tools. Identifies and recommends improvements.
Data management
- Devises and implements master data management processes, including classification, security, quality, ethical principles, retrieval, and retention processes.
- Derives data management structures and metadata to support consistency of information retrieval, combination, analysis, pattern recognition, and interpretation, throughout the organization.
- Plans effective data storage, sharing, and publishing within the organization.
- Independently validates external information from multiple sources.
- Assesses issues that might prevent the organization from making maximum use of its information assets.
Data visualization
- Applies a variety of visualization techniques and designs the content and appearance of data visuals.
- Operationalizes and automates activities for efficient and timely production of data visuals. Select appropriate visualization approaches from a range of applicable options.
- Contributes to exploration and experimentation in data visualization.
Data Science
- Applies existing data science techniques to new problems and datasets using specialized programming techniques.
- Selects from existing data sources and prepares data to be used by data science models.
- Evaluate the outcomes and performance of data science models. Identifies and implements opportunities to train and improve models and the data they use.
- Publishes and reports on model outputs to meet customer needs and conform to agreed standards.
Skills
- Excellent interpersonal, verbal, and written communication skills.
- A flexible attitude concerning work assignments and new learning.
- Ability to manage multiple and varied tasks with enthusiasm and prioritize workload with attention to detail.
- Must have the ability to work methodically in a fast-paced, time-sensitive environment.
- Demonstrable ability to apply analytical and critical thinking to problems and tasks.
- Ability to identify and implement process improvements.
- Proactively participates in skills improvement training and encourages their teams to participate.
- A self-starter and able to work under own initiative.
- Demonstrates effective application of knowledge.
- Proven ability to use Microsoft Office products (including Word, Excel & PowerPoint).
Knowledge and Experience:
- Experience using tools to communicate progress to Stakeholders.
- Experience with programming languages commonly used for data analysis (such as Python, and SQL).
- Experience with Business Intelligence tools (such as Power BI, and Tableau).
- Experience with Relational Databases.
- Experience with Statistical Analysis.
- Understanding of Agile methodologies (preferably Scrum) and UML.
- Awareness of Project Lifecycle and Project Management methodologies Modelling, Process Modelling, and/or other development methodologies.
- Experience in and knowledge of the life sciences sector.
- Solid Professional experience in the same or very similar role.
Education:
- Bachelor's Degree in a technical discipline (Math, Science, Engineering, Computing, etc.) or a related study, or equivalent project-related experience.
Note : Candidates from CRO or Pharma background can apply for the role.
