TICKL- Job Application

TL;DR: Imagine you are assigning coding skill points to your character in a game. You have 12 points to distribute among the different coding languages listed, reflecting your proficiency in that language; the more points you assign to a language, the more proficient you are in that language compared to others.

If you would like more detail: 

We would like to understand which coding languages you are most confident using. You have 12 points to allocate across the coding languages detailed below. The number of points you assign to a language should reflect how proficient you feel coding in that language, relative to the other languages (if any) you code in.

For example:

• If you have only coded in Python, you should allocate all 12 points to Python. 
• If you consider yourself to be equally proficient in coding in Python and SQL, you should allocate 6 points to Python and 6 points to SQL.
• If you consider yourself to be strongest at coding in Python, but you are also able to do some coding in both SQL and R, you might allocate 8 points to Python, and 2 points each to SQL and R. 

If a coding language you would like to allocate points to is not listed below, please allocate the points to "Other", and then provide additional detail in the text box provided.

TL;DR: Imagine you are assigning data skill points to your character in a game. You have 12 points to distribute among the different data-related skills listed, reflecting your proficiency in those skills; the more points you assign to a skill, the more proficient you are in that skill compared to others. 

If you would like more detail:

We would like to understand which data-related skills you are most confident using. You have 12 points to allocate across the skills detailed below. Just like the Coding Skills allocation above, the number of points you assign to a skill should indicate how proficient you feel in that skill, relative to the other skills you have experience with.

At a high-level, the following skills refer to experience with:

• Data Analysis: data manipulation and analysis to derive insights (typically involving structured datasets).
• Data Engineering: data cleaning, ETL processes, cloud computing, and designing, building and maintaining data pipelines and infrastructure.
• Data Science: machine learning, predictive modelling, and developing AI algorithms, to forecast trends and automate decision-making proceses.
• Data Visualisation: storytelling using tools like PowerBI / Qlik / Tableau / Looker to communicate insights and make data understandable.

If a skill you would like to allocate points to is not listed below, please allocate the points to "Other", and then provide additional detail in the text box provided.