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Individual Membership Application Form

Personal Information:

Tell us about your current analytics-related study




Professional Information:

  • Applies a range of foundational statistics (e.g. Regression or work on categorical analysis)
  • Plans and executes a manual and automated data cleaning strategy
  • Explains the benefits and disadvantages of methods for dealing with missing data (e.g. listwise deletion)
  • Explains risks of data collection and data bias
  • Embeds visualisations in data stories, making intentional choices and avoiding deception
  • Uses a mix of automation and manual work to create new features of data
  • Gets a data set ready for the machine learning pipeline
  • Reports confidence intervals and risk factors for all results
  • Plans, implements and reports on a strategy to normalise the data for machine learning
  • Works with the output of common machine learning models (regression, clustering, categorisation, anomaly detection, tree based models and association mining)
  • Explains analysis of unstructured data even if they don’t carry out the analysis
  • Identifies black boxed techniques and name some unintended consequences
  • Can explain key AI architecture (e.g. transformers) and name potential risks
  • Writes functions
  • Breaks down a complex problem using computational thinking
  • Protects data sets and the data within them
  • Links data work to business strategy and outcomes
  • Confidently manipulates and gains insight from downloaded and remote data sets
  • Chooses imputation methods intentionally
  • Makes connections across data sets efficiently and effectively
  • Carries out machine learning processes in a coded environment (R or Python)
  • Works with feature engineering to improve outputs
  • Demonstrates thorough understanding of deep learning frameworks and architectures either through practice or technical knowledge
  • Demonstrates advanced understanding of mathematics, statistics, probability, pattern detection and algorithm construction relevant to the analytical process
  • Uses SQL flexibly
  • Works within emerging and sometimes complex data and AI regulatory frameworks
Knowledge and Analytics
  • Works with a range of data structures on solutions to complex problems
  • Flexibly identifies environments to host solutions
  • Takes a systematic approach to data pipelines
  • Identifies strategies to work with new technology
    • Governance and Professionalism
    • Sets standards in the organisation for ethical data practices
    • Acts with integrity above and beyond own regulatory and legal jurisdictions
    • Constructively evaluates own work and peer work
    • Consistently operates within industry standards of interoperability
    • Actively promotes and implements sustainable product design
    Communication
    • Negotiates effectively
    • Creates quality visuals
    • Aligns to international standards of accessibility
    • Works to open science research standards
    • Builds effective external business relationships
    Leadership
    • Reliably contributes to company risk strategy
    • Identifies and critically evaluates assumptions
    • Empowers others beyond the organisation
    • Monitors developments
    • Contributes in a significant way to the organisation
Fellow Applicants will need to demonstrate their significant contribution to the field of analytics or wider society, such as:
  • The creation of an innovative product using analytics that has transformed the business environment
  • The creation of an innovative company, charity or social cause using analytics
  • Leading on an analytics project that has positively impacted your local community, wider society, or has addressed a social or environmental challenge
  • Outreach in the analytics community, particularly influencing those thinking about a career in analytics or those just starting their career
  • A significant contribution to the field of research in analytics or data science
  • A significant contribution to open source code or tools, or network infrastructure
  • A significant contribution to the development of government policy based on evidence through analytics
    • You will need to meet at least one of these 5 criteria as evidenced in your supporting documents:
    1. Has a record of solving complex and intractable problems and / or novel problems using innovative techniques.
    2 . Directs policy and leads the way in improving standards outside of own organisation.
    3 .Is a respected expert in the field evidenced through a body of work.
    4 .Influences policy and best practice beyond their own organisation.
    5 .Has made a significant contribution to the field beyond their own organisation.
    Evidence required to support your application to become an IoA Fellow:
    • A supporting statement which outlines the impact of your work and how you meet the criteria
    • An up-to-date CV
    • A link to Github, websites or profiles
    • Any other supporting documentation, such as list of publications
    • 2 letters of referral

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