name: review-linkedin-opportunity
description: Reviews inbound LinkedIn recruiter messages. Researches the likely company, role, compensation, and fit. Identifies the opportunity behind vague outreach using OSINT techniques. Use when user says "got a LinkedIn message", "recruiter reached out", "review this opportunity", or shares recruiter outreach text.
argument-hint:
Always read:
career/job-search/inbound-tracker.md— Read first: at-a-glance index of every prior approach, deduped by company. Tells you immediately whether this is a repeat (which company, which round) before you spend effort researching.career/job-search/context.md— Current search status, open loops, standing rulescareer/job-search/archive/inbound-2026-h1.md— Prior approach narratives + reply patterns (read when handling a repeat company)career/job-search/CLAUDE.md— Job search persona and strategycareer/CLAUDE.md— Career domain expertisecareer/context.md— Current role, compensation, prioritiescareer/job-search/recruiters.md— Known recruiter databasecareer/job-search/target-companies.md— Target company listcareer/reference.md— Compensation details, career historydecisions.md— Any settled career decisions
Read if relevant:
finances/context.md— If compensation comparison neededfinances/reference.md— Current total comp for comparison
2. Parse the Outreach
Extract every available signal from the recruiter message:
Direct Clues
- Recruiter name and firm — Search recruiter database, identify if specialist or generalist
- Job title — Exact title mentioned
- Company name — If disclosed
- Seniority signals — "leadership", "build a team", "strategic", "hands-on"
- Domain signals — Industry, tech stack, problem areas mentioned
- Company descriptors — "high-growth", "Series B", "profitable", "global expansion"
- Team size — "growing team of X", "first hire", "established function"
- Location/remote — Office requirements, hybrid policy
- Compensation hints — Salary range, equity, day rate
Indirect Clues (for identifying unnamed companies)
- Recruiter's other listings — Search the recruiter/firm's recent job postings
- Industry + descriptor combination — e.g., "high-growth fintech" + "newly created data function"
- Funding stage — Series A/B/C, PE-backed, profitable
- Team composition described — "6 data scientists", "80-person analytics team"
- Problem domains — "marketplace optimisation", "experimentation", "pricing"
- Geographic signals — HQ location, office locations, expansion markets
- Headcount — Approximate company size
- Retained vs contingent search — Retained (company-paid) suggests senior/exec role
3. Research the Opportunity
Run parallel research across multiple angles:
Identify the Company (if unnamed)
Strategy 1: Recruiter OSINT
- Search the recruiter's name + firm on LinkedIn, Google
- Check the recruiting firm's recent job listings (their website, LinkedIn, job boards)
- Look for matching roles on the firm's public job board
- Cross-reference job descriptions — retained searches often have near-identical wording
Strategy 2: Company Descriptor Matching
- Combine all descriptors (industry + stage + size + domain + location)
- Search for companies matching the profile
- Check recent funding rounds (Crunchbase, TechCrunch) that match the stage
- Look at VC portfolio company job boards if fund is mentioned
Strategy 3: Role Matching
- Search job boards for the exact title + industry
- Look for recently posted then removed listings (suggests retained search took over)
- Check LinkedIn Jobs for matching descriptions from different recruiters
Strategy 4: Market Context
- Research the sector's current hiring trends
- Identify which companies in that sector are in growth/build phase
- Check for recent news: funding rounds, leadership hires, expansion announcements
Research the Company (once identified or shortlisted)
For each candidate company, research:
- Growth & Funding — Recent funding, revenue trajectory, profitability, valuation
- Global Expansion — New markets, office openings, headcount growth
- Data/Analytics Function — Team size, maturity, tech stack, hiring patterns
- Tech Stack — dbt, Snowflake, BigQuery, Databricks, Looker, etc.
- Culture & WLB — Glassdoor reviews, flexible working, parental leave
- Leadership — Who runs data/DS, their background, reporting structure
- Compensation — Glassdoor, levels.fyi, market benchmarks for similar roles
- News — Recent press, blog posts, tech blog, conference talks
- Red Flags — Layoffs, leadership churn, Glassdoor complaints, funding concerns
Research the Recruiter
- Firm type: Executive search, specialist DS, generalist, internal?
- Reputation: Known in recruiter database? Specialist or spray-and-pray?
- Track record: What companies do they typically recruit for?
- Retained vs contingent: Retained = company paying upfront = serious search
4. Assess Fit
Rate the opportunity against Pedro's priorities:
Fit Dimensions
| Dimension | Weight | What to Assess |
|---|---|---|
| Role type | High | IC/advisory vs management? Pedro exploring IC/fractional direction |
| Compensation | High | Compare to current Meta all-in (~£375k). What's the realistic range? |
| Work-life balance | High | Flexible working, remote, hours culture, parental leave |
| Domain interest | Medium | Interesting DS problems? Experimentation, ML, causal inference? |
| Company trajectory | Medium | Growing, stable, or declining? PE exit pressure? |
| Timing | High | Baby due April 8, parental leave Apr-Aug 2026. Is timing viable? |
| Strategic value | Medium | Does this build toward Pedro's portfolio career goal? |
| Location | Medium | London commute feasible? Remote options? |
Timing Assessment
Always check against current timeline:
- Now → April 2026: Pre-baby, not exploring
- April → August 2026: Parental leave, completely unavailable
- September 2026+: Potential search window
If timing is wrong, assess whether to keep door open for later.
Compensation Comparison
Build a quick comparison table:
| Component | Current (Meta) | This Role (Est.) | Δ |
|-----------|---------------|-------------------|---|
| Base salary | £211k | £X | |
| Bonus | £X | £X | |
| RSUs/Equity | £X | £X | |
| **Total comp** | ~£375k | £X | |
| Day rate equiv | — | £X/day | |
For contract roles, calculate:
- Day rate × working days × take-home percentage
- Compare to perm equivalent and current comp
5. Format the Output
# LinkedIn Opportunity Review
## The Approach
**From**: {Recruiter name} ({Firm})
**Date**: {Date}
**Role**: {Title as described}
**Company**: {Named or "Unnamed — likely {Company}"}
## Company Identification
{If company unnamed, explain the detective work:}
- Clue 1: {descriptor} → narrows to {X}
- Clue 2: {recruiter's other listings} → points to {Y}
- Clue 3: {funding/size match} → confirms {Z}
**Confidence**: {High/Medium/Low}% — {Company Name}
{If multiple candidates, rank them with confidence percentages}
## Company Profile
| Attribute | Detail |
|-----------|--------|
| Company | {Name} |
| Industry | {Sector} |
| Stage | {Funding stage, revenue if known} |
| Headcount | {Approx} |
| HQ | {Location} |
| Data team | {Size, maturity} |
| Tech stack | {Known tools} |
| Remote policy | {Details} |
## Role Assessment
**What they're looking for**: {1-2 sentence summary}
**What this actually is**: {Honest read — is "Head of DS" actually a senior IC? Is "build from scratch" actually firefighting?}
## Fit Assessment
| Dimension | Rating | Notes |
|-----------|--------|-------|
| Role type | 🟢/🟡/🔴 | {IC vs management, scope} |
| Compensation | 🟢/🟡/🔴 | {Estimated range vs current} |
| Work-life balance | 🟢/🟡/🔴 | {Evidence from research} |
| Domain interest | 🟢/🟡/🔴 | {Problem space assessment} |
| Company trajectory | 🟢/🟡/🔴 | {Growth/risk assessment} |
| Timing | 🟢/🟡/🔴 | {Against parental leave timeline} |
| Strategic value | 🟢/🟡/🔴 | {Portfolio career alignment} |
## Compensation Estimate
| Component | Current (Meta) | This Role (Est.) | Δ |
|-----------|---------------|-------------------|---|
| Base | £211k | £X | -£X |
| Bonus | £X | £X | -£X |
| Equity | £X | £X | -£X |
| **Total** | ~£375k | ~£X | **-£X** |
{Context on whether comp cut is worth it for other gains}
## Verdict
**Overall**: {Worth pursuing / Keep door open / Polite decline}
{2-3 sentences: honest bottom line. Factor in timing, fit, compensation, and strategic value. Don't sugar-coat — if it's a bad fit, say so clearly.}
## Suggested Reply
{If worth replying, draft a response following voice-guide.md:}
- Matches Pedro's established reply pattern (polite, noncommittal, no parental leave mention)
- Appropriate level of door-opening based on fit assessment
---
*Sources: {List key sources used in research}*
6. Update Context
After the review:
- Update
career/job-search/inbound-tracker.md— if the company already has a row, bump its Round count and refresh Latest contact / Status / Next move (don't add a duplicate row); otherwise add a new one-line row. This is the dedup index. - Append the full approach narrative to the current half-year archive file (
career/job-search/archive/inbound-2026-h2.md, create if missing — same format asinbound-2026-h1.md): contact, date, role, company (confirmed or likely), fit assessment, reply status, market intel. Keepcontext.mdlean — it carries only the approach count, open loops, and standing rules. - If the approach leaves a follow-up hanging (e.g. "they'll revert in September", "decide whether to re-engage"), add an
⏳ **OPEN:**marker (tracker Open loops section and/orcontext.md) so/todaysurfaces it. - If a new recruiter is identified, consider adding to
career/job-search/recruiters.md
7. Draft Reply (if requested)
When drafting a reply:
- Read
voice-guide.mdfor Pedro's writing voice - Read
career/job-search/outreach-templates.mdfor established patterns - Match the tone of previous replies (see the inbound archive narratives)
- Key rules:
- Never mention parental leave (avoids "mercenary" optics)
- Polite but noncommittal unless genuinely interested
- Keep door open for September 2026+ if role has potential
- Short — 2-4 sentences for a standard decline/defer
Skip the identification detective work. Go straight to company research and fit assessment. Still research thoroughly — a named company doesn't mean the role is as described.
Multiple Candidate Companies
If the clues point to 2-3 possible companies:
- Research all candidates
- Present confidence-ranked list
- Highlight which clues favour which candidate
- Note what additional information would disambiguate
Internal Recruiter vs External
Internal recruiters (from the company itself) are a stronger signal:
- Someone specifically identified Pedro's profile
- Role is real and actively being filled
- May have more flexibility on timing
- Worth a warmer reply
External/agency recruiters may be:
- Spray-and-pray (red flag: generic message, no specifics)
- Retained search (strong signal: detailed brief, specific requirements)
- Contingent (moderate: they're racing other agencies)
Repeat Recruiter or Repeat Company
Check inbound-tracker.md first — it's deduped by company, so a repeat is obvious (e.g. DoorDash: Calum Ross → Rachel Quirk; Data Idols: two Courtney Moran approaches). Escalation from a manager-level recruiter to an executive one for the same company is a strong targeting signal — call it out.
- If the recruiter or company has contacted Pedro before, reference the previous interaction and bump the tracker Round count rather than treating it as net-new
- Note if it's a different client/role
- Adjust reply warmth accordingly (Courtney Moran pattern: shorter reply second time)
Role is Contract/Fractional
If the opportunity is contract or fractional:
- Use day rate benchmarks from recruiters.md
- Calculate IR35 implications
- Assess against portfolio career model (2-3 clients, 3 working days)
- Compare annual earnings to permanent equivalent
- Note: this aligns better with post-leave direction than permanent roles
Role is Clearly Wrong Fit
Don't overthink it. Quick assessment:
- State why it's not a fit (2-3 bullet points)
- Draft a polite one-liner decline
- Note if the recruiter is worth keeping warm for future roles
- Still log it in the inbound archive + tracker (pattern tracking is valuable)
Timing is Pre-Parental Leave
For any approach before September 2026:
- Default position: not exploring now
- Assess whether role/company is interesting enough to keep warm
- Draft door-open reply without mentioning parental leave
- Flag if this is a company to proactively contact in September
Suspicious or Low-Quality Outreach
Red flags to call out:
- Generic message with no role specifics
- Recruiter with no DS/data specialization
- "I came across your profile" + spray-and-pray signals
- Asking for CV before sharing any details
- Multiple recruiters from same firm (disorganized)
Recommendation: brief polite decline or ignore entirely.
The Approach
From: Daniel Wexler (Xcede) Date: March 4, 2026 Role: Data Science Manager Company: Unnamed — likely Relay (90% confidence)
Company Identification
Daniel didn't name the company, but the clues stack up:
- "High-growth Series A logistics tech" — narrows significantly
- ~120 people — matches Relay's reported headcount
- Domains: marketplace optimisation, courier performance, route estimation — logistics marketplace
- "One of Europe's largest logistics Series A" — Relay raised €33.4M (Plural-led), fits this description
- Ex-Stuart founders — confirmed via Crunchbase; Stuart was a major logistics platform
Confidence: 90% — Relay
Company Profile
| Attribute | Detail |
|---|---|
| Company | Relay (relay.delivery) |
| Industry | Logistics tech / last-mile delivery |
| Stage | Series A (€33.4M, Plural-led) |
| Headcount | ~120 |
| HQ | London |
| Data team | 6 data scientists (per recruiter) |
| Remote policy | Unknown — likely hybrid London |
Fit Assessment
| Dimension | Rating | Notes |
|---|---|---|
| Role type | 🟡 | Management (6 reports) — not IC/advisory direction |
| Compensation | 🔴 | Series A = likely £90-120k, massive cut from £375k |
| Work-life balance | 🟡 | Series A intensity, but smaller team = less process |
| Domain interest | 🟢 | Interesting DS problems (route optimisation, telematics) |
| Company trajectory | 🟡 | Tracking to Series B, but pre-PMF risk |
| Timing | 🔴 | 4 weeks before parental leave |
| Strategic value | 🟡 | Doesn't build toward portfolio/fractional career |
Verdict
Overall: Polite decline, keep door open
Interesting DS problems in a genuine growth-stage company, but wrong on almost every practical dimension: management not IC, massive comp cut, terrible timing. The team of 6 is smaller than current (17), which is appealing, but this is still a full-time management commitment at a fraction of the pay. Not worth disrupting parental leave plans.
Suggested Reply
Hi Daniel, thanks for thinking of me — the problems sound genuinely interesting (route estimation and network simulation especially). I'm not exploring new opportunities right now, but I'd be happy to stay in touch and hear about what comes across your desk later in the year.
Sources: Crunchbase (Relay funding), Xcede job listings, LinkedIn