Data Science Accelerator

Book an office hour appointment to discuss if the Data Science Accelerator or other CalData service offerings are right for you.


A 2020 internal survey found that approximately two-thirds of departments have yet to broadly adopt use of advanced analytics. The Data Science Accelerator is a way for you to harness the power of advanced analytics and applied statistics for a challenge you face in your agency or department.
Your department may already be using a variety of data tools and techniques, including dashboards, performance management, business process and policy changes, and root cause analysis. Or your department may have some existing statistical models, but has yet to really dive into using more advanced statistical and machine learning techniques.
The Data Science Accelerator helps teams tackle a business question or challenge using existing resources, data, and processes. Through a 1-4 month engagement, CalData’s Advanced Analytics & Evaluation team and your department will refine a problem, identify statistical methods to address it, and develop and institute a service change to improve your work.
The goal of this service is to both tackle a business question using data science and catalyze greater use of advanced analytics in your department. This service is based on a successful program launched by CalData staff while at the City and County of San Francisco.
Visit our showcase to see past public sector data science engagements and get a sense of the types of challenges data science is great at addressing
Watch a brief 7 minute presentation on the Data Science Accelerator to hear more about this service

How this service can help your department

To help you identify questions appropriate for data science, we created a list of problem types that we commonly see in the public sector. We encourage you to review each of these “problem typologies” and the supporting case studies.

Who is a good fit for this service

This service is for programs that have a business problem that fits into one of our problem typologies or some combination of these typologies. There is no need (or expectation!) for you to be technical or a data person. We encourage program-side leaders and staff to submit projects.

What this service includes

Over a 1-4 month period CalData’s Data Science team will work with you to refine your problem statement(s), conduct background research, identify appropriate data science approaches, and execute.
Typical Project Workflow
For more information on what to expect when engaging with the Data Science Accelerator, please refer to these blog posts:
A cornerstone of CalData’s Data Science work is the ethical use of data science. All projects will go through CalData’s Ethical AI toolkit.
To learn more, view a showcase of past projects that the core project team conducted while at the City and County of San Francisco: https://datasf.org/showcase/datascience/

Expectations of department partners

Below are the expectations departments will need to meet to use this service:
  • Commit to service change. First and foremost we expect departments to be open to and commit to a service change if that's where the analytics leads us.
  • Project Champion. To be an effective partner, we will need a Project Champion. The Project Champion is our liaison within the department who helps refine the problem statement and identify paths to service change. We estimate the Departmental Champion will need to dedicate on average 25% of their time to this project.
  • Data SMEs. We will need access to staff who best know the project data.
  • Commit to work within our timeframe. Engagements last between 1-4 months. The engagement will be an iterative process as we refine the original problem statement into something answerable with the data available and implementable within any service change constraints. If now is not a good time, we will have future cohorts.
  • Access to staff and business processes. As part of the engagement we expect to do user research. This may include 'ride-alongs', where members of the data science team shadow employees, interviews or other research methods. This will help identify relevant implementation factors that should be incorporated into the statistical model.
  • Timely data access. Please plan on preparing and working with your technology or database team to provide data.
  • Presenting and Disseminating. Part of our goal is to document and communicate what we learn and accomplish so both other departments and jurisdictions can benefit. We will need input and feedback and some participation from departments in this process.
Book an office hour appointment to discuss if the Analytics Accelerator is right for your problem. We are happy to help you think through if your challenge is a good match for data science