Chapter - Agile Development Methodology

Supplementary chapter prepared for the BWXT Data Science Workforce Training Pilot.

Outline in development. This chapter is scaffolded from the program's Module 1 objectives. The BWXT-specific parts — your team's ceremonies, tools, and roles — should be filled in with subject-matter experts. The general concepts below are ready to teach from.

About this chapter

Agile is a way of organizing work into short, repeating cycles so a team can deliver value early, learn quickly, and adapt. It is Module 1 of the program because it is the shared language and rhythm the whole cohort uses — including for the capstone project. This is a Tier 1 / Foundations capability: everyone is expected to understand the mindset and terminology.

The core idea: work in short cycles

Instead of planning everything up front and delivering once at the end, an Agile team works in sprints — short, fixed periods (often two weeks) that each produce something usable. Each sprint plans a small batch of work, builds it, reviews it, and reflects before the next.

What this chapter will cover

• Mindset and terminology — iterations, increments, "done", working software over documentation.
• The backlog and sprint planning — turning a wish-list into prioritized, sized work.
• Roles — product owner, scrum lead, and the team. (SME input: BWXT's role mapping.)
• Ceremonies — stand-ups, planning, review, retrospective. (SME input: BWXT's cadence and tools.)
• Applying Agile to data science — where DS work fits (and where it differs, e.g. uncertain research spikes).

Why it matters

Data science work is full of uncertainty — an approach may or may not pan out. Short cycles let the team try something, show it, and change direction before wasting weeks. The capstone runs in sprints for exactly this reason.