Careers in Data Analytics and Policy

About Me

• Program Director at Johns Hopkins University for the M.S. in Data Analytics and Policy.
• M.S. degree - an interdisciplinary professional master’s degree that prepares learners for careers in the public sector.

Plan for Presentation

• Defining Data Science.
• The Hard Skill Toolkit.
• Career Roles & Archetypes.
• The Public Sector Landscape: Where the jobs are.
• Unique Aspects and Challenges of Public Sector Data, and how to prepare.
• The Job Search.

What is Data Science?

• At its core: Using math, statistics, and programming to extract insights from raw information.
• It is a discipline of translation—moving from numbers to narratives.
• Every organization benefits from this.

The Different Branches

• Exploratory Analysis (Description): What is happening?
• Econometrics (Inference): Focused on understanding causality (cause and effect). It is theory-driven and rooted in social science.
• Machine Learning (Prediction): Focused on maximizing predictive accuracy and identifying patterns; rooted in computer science.
• Do you need to get information, isolate a specific effect for a decision, or do you need a predictive engine that works at scale? (or, all three)

Career Roles & Archetypes

• Data Analyst: Telling stories through visualization and reporting.
• Data Scientist: Building models to anticipate and solve community needs.
• Evaluator: Designing studies to see “what actually works.”
• Data Engineer: Managing the plumbing to ensure data is clean, accessible, and secure.

The Public Sector Landscape

• Federal Agencies: Large scale data at the Census, BLS, HHS, and more.
• State & Local Government: Where policy hits the pavement - housing, transit, public health, public safety.
• Civic Tech & Research: Think tanks like the Urban Institute, NGOs.
• The Hybrid Space: Consulting for social impact, governmental operations, and advocacy work (and profit).

Unique Aspects of Public Sector Data

Unique Aspects of Public Sector Data

• Mismatch between Evidence and Politics
• Transparency and Legalities
• Limited Resources

Mismatch between Evidence and Politics

• Experts are ignored all the time.

• Technical success vs. political failure:

  • Lack of buy-in from frontline workers or the community.
  • Differing incentives and interests of political decision makers and substantive experts.

Transparency and Legalities

• Thinking of data as a public utility rather than a corporate asset.
• The responsibility of the data steward: accuracy, transparency, and accountability.
• High stakes decisions may need human touch.

Working Lean

• Many agencies operate on legacy systems, Excel spreadsheets, or even paper records.
• Infrastructure is often fragmented; data silos are the norm.
• In a low-tech environment, a little skill goes a long way.
• Easy win: Automating a 20-hour manual reporting task with a simple script can be revolutionary for a small agency.

Navigating the Job Search

• Build a portfolio
• Start locally
• Look for experiences and fellowships
• Approach job boards (including USAJOBS) with caution
• “Job Search” is often the wrong word - it’s about relationship search.
• Get a job!