Coach — CareerAgent

Funnel

817

new

shortlisted

applied

interview

rejected

offer

skipped

2 of 818 jobs scored · German likely required in 100% of scored postings

Search queries — what the market gives you

Search	Jobs	Scored	Avg score
Machine Learning Engineer	36	2	26.5
hellofresh	378	0	–
celonis	230	0	–
Software Engineer Python	56	0	–
Data Engineer	41	0	–
AI Engineer	77	0	–

Coaching report

Generated 2026-07-15 · openai/gpt-5

Your current funnel is 100% German-required and senior-leaning; fix the incomplete profile and pivot searches to Werkstudent/junior, English-language roles via broader sources this week.

Market fit

179 new roles ingested, but only 2 were scored; coverage is too low to find matches.
All current roles appear to require German (german_required_rate: 1.0) — misaligned with your A2 level.
For 'Machine Learning Engineer' searches: avg score 26.5 with 0 good/strong matches — primarily seniority and language mismatches (see top_concerns).
Source skew: 179/179 from Bundesagentur für Arbeit (BA), which tends to skew German-language and senior/full-time; no Greenhouse/Lever/Adzuna intake in this batch.

Prioritize: Werkstudent Machine Learning/Data/AI (English-friendly), AI/ML Intern (Germany), Junior Python Backend Engineer, Junior Data Engineer, Master Thesis (Machine Learning/AI) / ‘Masterarbeit KI’

With BA-only intake, 100% of roles flagged as German-required. At A2, near-term traction will come from English-language teams and student/junior postings. Expand sources (Greenhouse/Lever/Adzuna) and explicitly target Werkstudent/Intern/Junior queries; pursue German upskilling in parallel, but don’t wait for B2 to build pipeline.

Application performance

No applications with outcomes yet; you’re still in pipeline-building mode.

Profile recommendations

Remove every 'FILL IN' placeholder this week: add university names/locations, B.Sc. details, employer names, dates, and tech for each role. Incomplete sections will tank ATS scoring and match rates.
Publish the CareerAgent project to GitHub and add the repo URL in the profile links. Include a README with stack, architecture, and screenshots.
Rewrite headline to: “M.Sc. AI student | Python/ML | Open to Werkstudent/Junior roles in Germany”. Lead the summary with Python, ML tooling (PyTorch, scikit-learn), and any production/deployment you’ve done.
Add a work authorization line at the top: “Student visa (eligible for part-time work) • 18‑month post‑graduation job-seeker visa.” If you can legally work 20h/week during semester, state it explicitly.
Create two CV variants: (1) ML/AI focus; (2) Python Backend/Data focus. Each should have 4–6 quantified bullets highlighting Python, Docker, REST, SQL, and ML workflows you’ve actually used.
Expand Projects: add 1–2 small, shippable items (e.g., ML model served via FastAPI + Docker, basic CI, evaluation metrics). Link code and, if possible, a live demo. Only list tech you actually used.
Keep language honest: English C1, German A2. Don’t claim B1/B2. If you enroll in a course, you can add “German A2 (actively improving)” — otherwise leave as-is.

Do this week

Enable additional sources in your job agent and rerun nightly ingestion: Adzuna + Greenhouse + Lever (current batch is BA-only). Verify next run shows >0 jobs from these sources.
Add these search queries (exact text) to target English-friendly/student/junior roles: 1) "Werkstudent Machine Learning" 2) "Werkstudent Data Science" 3) "Werkstudent AI" 4) "Werkstudent Python" 5) "Praktikum Machine Learning" 6) "Praktikum Data Science" 7) "Junior Machine Learning Engineer" 8) "Junior Data Engineer" 9) "Junior Python Backend" 10) "AI Engineer English Germany" 11) "Masterarbeit KI" 12) "Thesis Machine Learning Germany".
Add exclusion filters to cut noise: exclude keywords "Senior", "Lead", "Principal", "Staff", "Manager", and German phrases like "5+ Jahre", "Berufserfahrung 5+", "Teamleiter". Also include keyword "English" where your engine supports it.
Increase scoring coverage: score all jobs from all added searches. Target a shortlist of at least 12 roles with match score ≥55 within 7 days.
Apply this week to the first 6–8 shortlisted roles that are Werkstudent/Intern/Junior and score ≥60. Tailor the CV variant to the role (ML vs Python/Data) and include your GitHub link.
Complete profile fixes: replace all 'FILL IN' items, add GitHub/LinkedIn URLs, and add the CareerAgent repo link — deadline: end of this week.