Statistical Data Scientist

Role Overview

• Collect, clean and process data from various sources.
• Conduct statistical analysis and build statistical models or machine learning algorithms to derive actionable insights.
• Develop and deploy predictive models and algorithms to solve business and operational challenges.
• Create visualisations, including interactive maps and dashboards, as well as reports to communicate data insights effectively.
• Stay up-to-date with the latest advancements in statistics and data science and apply them to enhance analytics solutions.
• Work cross-functionally with teams to integrate statistical analysis and products into existing workflows and systems.
• Provide expert guidance and support to internal and external stakeholders on data science projects.

Requirements

• Statistics & mathematics skills (probability, statistics, uncertainty, linear algebra and calculus).
• Confident using probability, statistics and mathematics to design and develop solutions for real-world problems that can be integrated into existing workflows and systems.
• Machine Learning skills (working with large datasets, data transformations, data and metadata cleaning and maintenance).
• Demonstrable experience in applications of classification, clustering, dimension reduction and other machine learning methods and algorithms to produce useable outcomes, including rigorous quantitative assessment of performance.
• Computing skills (strong programming skills, understanding of good programming practices, standards and paradigms).
• Experience working in a collaborative coding environment that is attentive to creating efficient and maintainable code.
• Solid understanding of machine learning life cycles, operations and industry standard tools/practices.
• Experience writing code that is efficient and optimised for the development of research code and production code.
• Experience using software development tools such as VS Code, Conda and GitHub.
• Experience working with command line tools and Unix based operating systems.
• You must be conversant with Python and R, both for code development and deployment of machine learning models and algorithms in a cloud environment (preferably Azure), including writing code for parallel processing and distributed processing to scale up computations.
• Experience working with databases and with internal and external APIs (internal software, databases and cloud services).
• Experience in using other languages, such as HTML and JavaScript, is desirable but not essential.
• Soft skills (upfront, open, teachable, able to learn and re-learn, have impeccable professional integrity, and aspire to high standards and personal excellence)
• Excellent problem-solving and analytical skills, attention to detail, and far-sightedness to anticipate global consequences of local actions.
• Able to adapt and keep up with the fast-paced technology environment.
• Ability to work in a dynamic commercial environment where tight deadlines are common and can align technical and commercial requirements.
• Able to work effectively with others in cross-functional teams and collaborate with stakeholders from different disciplines. You must therefore have strong verbal and written communication skills, including the ability to communicate complex technical concepts to non-technical audiences.

Tech Stack

• Azure
• Cloud
• JavaScript
• Python
• Unix

Benefits

• Flexible work arrangements