Opportunity Radar: Singapore AI & FinTech Opportunity Intelligence System

Opportunity Radar is a local-first opportunity intelligence system for technical, research, data, and engineering professionals exploring Singapore AI, FinTech, RegTech, risk analytics, data analytics, and digital transformation opportunities.

It converts curated job, policy, company, event, learning, and side-hustle signals into structured weekly opportunity briefs with relevance scoring, actionability scoring, suggested next actions, and source lists.

It is built to be auditable: inputs can be validated, report dates can be fixed for reproducibility, and runtime outputs can be isolated from curated examples.

The project is designed as a portfolio-ready prototype and a foundation for a future newsletter, consulting service, or opportunity intelligence product.

Opportunity Radar helps career switchers and technical professionals turn fragmented opportunity signals into a weekly action plan.

Instead of showing raw job feeds, it organizes curated signals into role families, company watchlists, project ideas, learning priorities, and concrete next actions.

Opportunity Radar does not provide job guarantees, immigration advice, legal advice, investment advice, automated job applications, or automated outreach services.

Why This Project Matters

Opportunity discovery is often fragmented across job boards, company pages, policy announcements, events, newsletters, and informal communities.

For people transitioning into AI, FinTech, RegTech, data analytics, or digital transformation roles, the hard part is not only finding information. The hard part is deciding:

• which signals are relevant;
• which roles fit their background;
• which skills to prioritize;
• which companies to watch;
• which portfolio project to build next;
• what action to take this week.

Opportunity Radar turns these fragmented signals into a structured weekly opportunity brief.

Target Users

Opportunity Radar is designed for:

• research professionals transitioning into AI / data / FinTech roles;
• engineers exploring Singapore opportunities;
• data analysts looking for FinTech or RegTech roles;
• AI application builders looking for business ideas;
• professionals who want a weekly opportunity brief rather than raw job feeds.

What It Does

• imports curated job, policy, event, company, learning, and side-hustle signals;
• normalizes them into a common OpportunityItem schema;
• deduplicates similar items;
• classifies items by category;
• scores relevance, actionability, freshness, credibility, and uniqueness;
• ranks opportunities;
• generates English and Chinese weekly reports;
• provides a simple Streamlit dashboard.

What It Does Not Do

• does not scrape LinkedIn;
• does not bypass login pages;
• does not auto-apply to jobs;
• does not provide immigration or legal advice;
• does not provide investment advice;
• does not guarantee job outcomes;
• does not collect private personal data.

Architecture

Opportunity Radar uses a deterministic local pipeline:

manual CSV/YAML inputs
  -> import and normalize
  -> deduplicate and classify
  -> score and rank
  -> build report context
  -> write Markdown, HTML, and JSON
  -> inspect in Streamlit

Quick Start

cd opportunity-radar
python -m pip install -e .[dev]
python -m opportunity_radar.main validate --input-dir examples/sample_inputs
python -m opportunity_radar.main generate --profile singapore_ai_fintech --mock --as-of 2026-07-06

Without installing the package, run:

$env:PYTHONPATH="src"
python -m opportunity_radar.main generate --profile singapore_ai_fintech --mock

CLI Commands

Generate from bundled synthetic sample inputs:

python -m opportunity_radar.main generate --profile singapore_ai_fintech --mock

Validate manual inputs:

python -m opportunity_radar.main validate --input-dir examples/sample_inputs

Generate from a manual input directory:

python -m opportunity_radar.main generate --profile singapore_ai_fintech --input-dir examples/sample_inputs

Generate with a fixed report date:

python -m opportunity_radar.main generate --profile singapore_ai_fintech --mock --as-of 2026-07-06

Generate into an isolated output directory:

python -m opportunity_radar.main generate --profile singapore_ai_fintech --mock --as-of 2026-07-06 --output-root .tmp/opportunity-radar-output

Generate with strict validation:

python -m opportunity_radar.main generate --profile singapore_ai_fintech --input-dir examples/sample_inputs --strict-validation --as-of 2026-07-06 --output-root .tmp/validated-output

Generate and refresh stable examples:

python -m opportunity_radar.main generate --profile singapore_ai_fintech --mock --as-of 2026-07-06 --copy-samples

Expected outputs:

data/processed/YYYY-MM-DD_singapore_ai_fintech.json
reports/json/YYYY-MM-DD_singapore_ai_fintech.json
reports/markdown/YYYY-MM-DD_singapore_ai_fintech_en.md
reports/markdown/YYYY-MM-DD_singapore_ai_fintech_zh.md
reports/html/YYYY-MM-DD_singapore_ai_fintech_en.html
reports/html/YYYY-MM-DD_singapore_ai_fintech_zh.html

Local Demo Script

After installing the project, you can run the local demo workflow:

python scripts/run_demo.py

The PowerShell wrapper also delegates to the same cross-platform script:

.\scripts\run_demo.ps1

Dashboard

streamlit run src/opportunity_radar/dashboard/app.py

The dashboard loads generated reports first and falls back to curated sample outputs. It includes category filters, a minimum score slider, keyword search, score charts, link columns when supported by Streamlit, and a Markdown report preview.

Screenshots

Screenshots can be generated by running the dashboard locally:

streamlit run src/opportunity_radar/dashboard/app.py

Suggested screenshots:

• the Opportunity Dashboard;
• the generated weekly opportunity report;
• category and score distributions.

Sample Inputs

The sample inputs are synthetic, Singapore-focused, and safe to publish:

• examples/sample_inputs/singapore_ai_fintech_jobs.csv
• examples/sample_inputs/sample_policy_signals.yaml
• examples/sample_inputs/sample_events.yaml
• examples/sample_inputs/sample_side_hustle_ideas.yaml
• examples/sample_inputs/sample_company_signals.yaml

Sample Reports

• English weekly sample report
• Chinese weekly sample report
• Sample JSON output

Documentation

• Methodology
• Input schema
• Changelog

Scoring Formula

final_score =
  0.30 * relevance_score
+ 0.25 * actionability_score
+ 0.20 * freshness_score
+ 0.15 * credibility_score
+ 0.10 * uniqueness_score

• relevance_score: how closely the opportunity matches the selected audience profile.
• actionability_score: whether the item suggests a clear next step such as apply, register, build, learn, or contact.
• freshness_score: how recent the opportunity signal is.
• credibility_score: reliability of the source type.
• uniqueness_score: whether the item adds distinct value rather than duplicating other signals.

Repository Structure

config/                 Profiles, sources, scoring rules, report template
docs/screenshots/       Placeholder for future dashboard and report screenshots
examples/sample_inputs/ Synthetic CSV/YAML demo inputs
examples/sample_reports Curated stable sample Markdown reports
examples/sample_outputs Curated stable sample JSON output
src/opportunity_radar/  Models, pipeline, writers, CLI, dashboard
tests/                  Pytest suite
reports/                Generated Markdown/HTML/JSON outputs, ignored by Git
data/processed/         Generated processed JSON, ignored by Git

Repository Hygiene

Generated reports and processed data are intentionally ignored by Git:

• reports/
• data/processed/
• data/cache/

Curated examples are stored under:

• examples/sample_inputs/
• examples/sample_reports/
• examples/sample_outputs/

Tests

pytest

Local Verification

Before committing changes, run:

ruff check .
python -m compileall src tests scripts
mypy src/opportunity_radar
pytest
python -m opportunity_radar.main validate --input-dir examples/sample_inputs
python -m opportunity_radar.main generate --profile singapore_ai_fintech --mock --as-of 2026-07-06 --output-root .tmp/final-check
python scripts/verify_line_endings.py

Disclaimer

Opportunity Radar is an informational opportunity intelligence prototype. It does not provide job guarantees, immigration advice, legal advice, investment advice, automated job application services, or automated outreach services.

Release Status

Current release: v0.2.0.

Opportunity Radar v0.2.0 is a local-first Singapore AI / FinTech / RegTech opportunity intelligence prototype. It supports deterministic report generation, manual input validation, isolated output roots, English and Chinese reports, and a Streamlit dashboard.

This project is informational. It does not provide job guarantees, immigration advice, legal advice, investment advice, automated job applications, or automated outreach.