Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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FlyRank Internship — Starter Dataset (Anonymized)

The public, safe starting point for the FlyRank Applied Search Intelligence ML internship. 30,000 anonymized content-performance rows across 32 pseudonymized clients (53 columns).

Public-safe: hashed content_id / client_id + numeric/categorical metrics only — no titles, URLs, keywords, domains, or client names.

What it's for

Week 1–2 quick wins and the ready-now capstone lanes (ranking-signal analysis, lifecycle / opportunity scoring, content-archetype clustering).

Verified reference results (this 30k slice)

Rule baseline Precision@50 = 0.26 → Random Forest Precision@50 = 0.74
search_volume vs impressions_90d correlation ≈ 0.0012 (essentially zero — a real myth-buster)
Weighted CTR by position: top_3 0.49% → page_1 0.35% → deep 0.04%
Length is not the differentiator: growing vs declining word count ≈ 2,850 vs 2,910

Safety rules

Anonymized, but still treat row-level outputs as not-for-careless-publishing. Do not use product flags (health_score, needs_ctr_fix, is_quick_win, …) as model features — they leak the decline label. Keep all public outputs anonymized/aggregate.

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