When we want to use data to solve a problem you care about, our first step is to define your problem. Our second step is to determine the people affected by your problem, and what a meaningful solution looks like to them. Only then do we think about how data science can help.
This recipe allows us to approach your problem with intent—once we know what the problem you care about is and what a meaningful solution looks like to the people affected by it, we can work backward to figure out the data, analyses, and tools needed to solve your problem. By framing your problem this way we can use data science to develop better solutions for you and your audience.
Your data strategy describes all of the ways you get, store, manage, share, and use data. A good data strategy makes data accessible and usable to the people who need it.
I can help you make data more accessible and usable for solving problems you care about by:
- Identifying data sources
- Identifying data problems
- Teaching data literacy
- Cleaning and transforming data
Your data story describes how you build and share knowledge from data. A good data story helps you and your audience understand and trust the implications of your data, then develops data informed solutions for the problems you care about.
I can help you develop data informed solutions for the problems you care about through:
- Exploratory data analysis
- Data visualization
- Statistical modelling
- R package development
- R Shiny development
Your data ethics framework describes the values and principles you follow to use data responsibly. A good data ethics framework considers the social and ethical implications of using data at every stage of your project, and develops solutions that safeguard and promote the wellbeing of your audience.
I make data ethics a priority when helping you with your data strategy and data story so you can use data for good.
I am available for consulting work and private training to help you solve the problems you care about at any point in your project lifecycle.
Developing or evaluating your data strategy and data story.
Short or long term.
Negotiable by project and typically billed hourly.
Developing you or your team's data science and R programming skills.
Single or series of workshops or meetings.
Negotiable by training and typically billed per-session for smaller scope or hourly for larger scope.