Data EngineeringFDE career entry and client-delivery practice

Build a portfolio around evidence rather than screenshots

PK
Pankit Kumar
Sr. Data Scientist at Parexel (a Goldman Sachs–backed company) · 20 September 2026 · 2 min read
Technically reviewed by Ishaan Sharma
In this article (3 sections)

A screenshot proves that one screen existed. A reviewer needs to see the problem, decisions, executable checks and recovery path.

Inspect an evidence map

The delivery lab builds a fictional portfolio record.

python
from delivery_cases import portfolio_case

result = portfolio_case()
assert result["screenshots_only"] is False
assert result["claims_supported"] is True
assert result["external_client_work"] is False
assert result["reviewer"] == "pending"

Lead with a concise problem and scope. Link source/data manifest, runnable repository, setup, architecture, ADRs, tests/evals, results, logs/health, threat model, cost, demo and runbook. Include one failure and repair. Label fixtures, mocks, local deployment and fictional-client work.

Use screenshots or video to aid navigation, not replace source evidence. Remove secrets and personal data. State your individual contribution and unresolved limits. Do not turn course work into invented employment or business outcomes.

The FDE for Freshers course builds ten-plus artifacts and a fictional engagement around verifiable work.

Exercise

Audit one project claim by claim. For every sentence, link evidence or weaken/remove it. Ask a peer to reproduce the normal and failure demo.

Continue learning

This article is part of the FDE career entry and client-delivery practice sequence. Use the neighbouring tasks when you need the prerequisite or the next application.

Reference: GOV.UK service assessment guidance.

PK
Pankit Kumar
Lead Instructor, NeuraPath Academy

Pankit Kumar has 10 years in Data Science & AI, building and shipping production systems in regulated pharma and clinical environments. He is a freelance trainer at Boston Institute of Analytics, AnalytixLabs and Scaler, and has taught this material to thousands of working professionals.

This article is part of our FDE for Freshers programme — 6–7 months. Build your engineering foundations, then take AI from discovery to delivery.

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