[ANALYSIS_REPORT] The provided resume section is empty. Although the candidate is described as a fast learner with self-hosting and trading experience in the context, no specific technical skills or experience could be verified against the strict Data Engineering requirements (Scala, Spark, Cloud, Medallion Architecture) to justify a score.

[ANALYSIS_REPORT] The resume content is empty. While the candidate has positive demographic and 'fast learner' traits, no hard skills or experience were provided to evaluate against the requirements (Python, AWS, AI/LLM, etc.).

[ANALYSIS_REPORT] Candidate is significantly overqualified for this Level I/Analyst role. He possesses the required Engineering degree (Mechatronics) and Fluent English. His advanced data analysis skills (Python, Pandas, Algorithmic Trading) far exceed the 'Intermediate Excel/Power BI' requirement. While 'Power BI' is a keyword gap, his background in Supply Chain Analytics and Financial modeling ensures he can master it immediately.

[ANALYSIS_REPORT] Candidate matches all core hard skills: Python (Pandas/DataFrames), SQL (transferable to PostgreSQL), AWS familiarity, and CI/CD. The candidate's practical experience with 'production-grade' systems and 'self-hosted AI' demonstrates the required Machine Learning and data pipeline capabilities (ETL). The only deviation is the 'nice-to-have' MSc/PhD academic background, but the MicroMasters and proven 'Fast Learner' ability (self-taught AI/Trading systems) strongly compensate.

[ANALYSIS_REPORT] Candidate provided no resume content in the <resume> tags. Based solely on the 'Fast Learner' context (Self-hosted LLMs, Algorithmic Trading), we can infer technical aptitude and likely familiarity with Docker/Git (common in self-hosting) and possibly Python. However, the role is a Senior Java Architect position requiring a deep legacy and modern Java stack (JSF, Struts, Spring Boot) and Frontend (Angular/React Native) which are not evidenced. The score reflects potential ('Fast Learner') but massive skill gaps for a senior architectural role.

[ANALYSIS_REPORT] Strong alignment with the specific 'AI Focus' of the role, backed by proven experience in self-hosted LLMs and automation (Python). The candidate fits the 'Fast Learner' profile well for architectural concepts. Main gaps are in the traditional enterprise stack (Java/Kotlin, Oracle), but their specialized AI/Infra skills likely outweigh this for this specific strategic role.

[ANALYSIS_REPORT] Strong foundational match in AI/LLMs and Python. The candidate's experience self-hosting LLMs demonstrates deep technical capability that likely exceeds simple API integration (Bedrock/GPT). However, there are specific stack gaps: the resume lists 'AWS Basics' while the role demands specific AWS AI services (SageMaker, Bedrock). Additionally, the candidate focuses on Text/LLMs, while the role explicitly requires Multimodal (Image/Video/Stable Diffusion) experience.

[ANALYSIS_REPORT] Strong domain alignment with the 'Chatbot & IA' requirement due to self-hosted LLM experience, covering Prompt Engineering and NLP concepts deeply. The 'Fast Learner' trait and algorithmic trading background imply strong logic and API integration skills. However, the resume is effectively empty regarding the specific mandatory tech stack (Java, JavaScript) and databases (Oracle, MariaDB), which are critical for a Mid-level (Pleno) role to hit the ground running.

[ANALYSIS_REPORT] Resume text was empty; evaluation relies on 'Fast Learner Context'. Candidate's background in 'Self-hosted LLMs' and 'Algorithmic Trading' provides strong evidence for Python ecosystem, Deep Learning, NLP, and Time Series Analysis requirements. However, critical enterprise-grade skills (SQL, Kubernetes, Cloud Platforms) are not explicitly confirmed in the context, representing significant but bridgeable gaps for a Senior role.

[ANALYSIS_REPORT] Strong match for the specific 'Modern AI' and 'Agentic Systems' requirements. The candidate's background in Quant Trading and Self-Hosted LLMs aligns perfectly with the 'RAG, MCP, and embedding-based semantic search' goals. While he lacks the formal '5+ years Data Scientist' title and specific Big Data keywords (Spark), his founder-level autonomy and deep integration experience suggest he can handle the architectural and implementation demands better than a pure academic Data Scientist. The 'Fast Learner' trait bridges the gap for specific libraries like Scikit-learn.

[ANALYSIS_REPORT] Candidate is a strong Systems/Backend Generalist with proven capacity for complex self-learning (LLMs, Algorithmic Trading). However, the specific tech stack is a mismatch: the role requires Advanced Golang/TypeScript and Event Streaming (Kafka), while the candidate is primarily Python-focused. The foundational skills (Docker, APIs, Architecture) are present, but the specific languages and orchestration tools (K8s vs Local Clusters) represent a learning curve.

[ANALYSIS_REPORT] Candidate is a strong 'Fast Learner' match. While lacking the specific stack (Golang, K8s, Kafka), the JD explicitly allows for a 'proven ability to quickly ramp up' on Golang. The candidate's background in building complex, self-hosted AI clusters and algorithmic trading systems demonstrates the required architectural depth and rapid learning ability. He possesses the core backend requirements (SQL, Docker, API design, Linux) but will need to bridge the gap to Cloudflare's specific toolset.

[ANALYSIS_REPORT] Candidate meets all educational (Engineering) and analytical requirements, significantly exceeding the 'Excel' requirement with Python/Pandas expertise which indicates superior data handling capabilities. Strong background in financial logic and risk management. The primary gaps are specific domain knowledge in Distressed Assets/Bankruptcy (Recuperação Judicial) and explicit deep-dive Accounting proficiency, though the candidate's 'Financial Analyst' experience and 'Fast Learner' trait suggest these can be bridged quickly.

[ANALYSIS_REPORT] The candidate has a strong foundation in Infrastructure-as-Code (Terraform) and system automation (Python), demonstrating the 'Fast Learner' trait via self-hosted AI projects. However, there is a significant stack mismatch: the role requires Node.js and specific Mobile CI/CD experience (App Center, Bitrise), whereas the candidate is Python/Data-centric. Additionally, the candidate lists 'AWS Basics', while the role requires full Cloud Administration.

[ANALYSIS_REPORT] Fundamental domain mismatch. The candidate is a Software/Systems Architect specializing in AI and Supply Chain, while the role is for a Senior Civil/Construction Design Engineer. Despite the Engineering degree, the candidate lacks the entire required toolset (Revit, AutoCAD, BIM) and specific industry experience (Construction, HVAC, Hydraulics) mandated for this Senior-level role.

[ANALYSIS_REPORT] The candidate is a strong technical architect with solid SQL, database, and process automation experience (Python, SDLC), which aligns with the logical requirements of the role. However, the position is specifically for a specialist in the Microsoft Power Platform ecosystem, a domain completely absent from the resume. While the candidate's 'Fast Learner' profile suggests they could master this low-code stack quickly, they currently lack the primary hard skill required.

[ANALYSIS_REPORT] Strong match on core Python experience (6+ years) and engineering mindset. The candidate's background in automation, data pipelines (Pandas/NumPy), and self-hosted infrastructure aligns well with Data Engineering. However, the role leans heavily into Backend Web Development (Django/Flask) and Container Orchestration (Kubernetes), which are not explicitly detailed in the resume. 'AWS Basics' is a potential weakness for a Senior Cloud role, but his 'Fast Learner' trait with complex self-hosted systems suggests rapid upskilling capability.

[ANALYSIS_REPORT] Strong match for the core automation and Python requirements. The candidate is a high-code automation architect (Python, APIs, Docker, AI) capable of complex logic. The primary gap is specific enterprise 'Low-Code' RPA platforms (Power Automate, UiPath) and specific UI automation libraries (Selenium), but given his experience building JIT engines and AI clusters, these are trivial for him to acquire. He exceeds the architectural and integration requirements.

[ANALYSIS_REPORT] The candidate has strong foundational skills in automation (Python), Infrastructure as Code (Terraform), and containerization (Docker), which aligns well with DevOps culture. However, the role is a Senior Specialist position requiring 'Deep practical knowledge' in orchestration (Kubernetes/OpenShift) and API management (Kong/3scale), whereas the candidate lists 'AWS Basics' and 'Local AI Clusters'. While the candidate is a fast learner with self-hosted system experience, the gap between 'Basics' and the deep production expertise required for OpenShift/K8s and Cloud Administration is significant for a senior specialist role.

[ANALYSIS_REPORT] Candidate demonstrates strong architectural ownership and 'figure it out' capability (Self-hosted AI, Trading Bots) which aligns well with the 'Identity Foundation' and architectural requirements. Significant overlap in Domain (SSO, RBAC, Auth). The primary gap is the specific tech stack: the role targets high-concurrency compiled languages (Java/Kotlin/Go) and enterprise message brokers, whereas the candidate is a Python/Scripting expert.

[ANALYSIS_REPORT] The candidate has a strong technical background in Systems Architecture, Cloud/Infrastructure (AWS, Docker, Terraform), and Backend Logic (SQL, Algorithms, Python), which covers many auxiliary requirements. However, the primary hard skill for this specific role—the .NET/C# ecosystem—is completely absent from the resume. While the 'Fast Learner' trait and engineering degree suggest they could learn it (and the role is 'Junior'), the immediate stack mismatch is significant.

[ANALYSIS_REPORT] The candidate has a strong foundation in core infrastructure concepts (Terraform, Docker, Systems Architecture) and a unique advantage for the 'FinOps' requirement due to their background in Financial Analysis. However, the role specifically demands 'In-depth knowledge of Google Cloud Platform' and 'GKE', while the candidate currently lists 'AWS Basics' and local clustering. While cloud concepts transfer, the specific expertise in the Google ecosystem is a significant gap for a Senior Specialist role.

[ANALYSIS_REPORT] Strong match due to the unique combination of 'Mechatronics Engineering' (covering Math/Physics foundations), 'Supply Chain Analytics' (MITx), and proven algorithmic experience (Crypto trading bots, JIT logic). While 'Pattern Recognition' and professional 'Physics' usage aren't explicitly detailed as recent daily tasks, the candidate's engineering background and algorithmic trading experience strongly suggest competence. The logistics domain expertise is a significant value-add for this specific role.

[ANALYSIS_REPORT] Significant domain mismatch. Candidate is a high-level Systems/Cloud Architect (Python, Docker, AWS) applying for a low-level Systems/Embedded role (C++, Drivers, USB). While the Mechatronics degree (2014) and recent AI hardware tinkering suggest potential aptitude and foundational knowledge, the resume lacks professional experience in the core requirements: C++, CMake, and Computer Vision. The 'Fast Learner' trait is strong, but the gap between Web/Data Automation and C++ Device Integration is substantial.

[ANALYSIS_REPORT] Strong match for the Supply Chain and operational efficiency aspects, backed by advanced data engineering skills (Python/SQL) that likely exceed the requested Power Automate/Query proficiency. However, the specific requirement for 'Power BI Advanced' and 'ESG/Sustainability' frameworks represents a tooling and domain gap, though the candidate's 'Fast Learner' profile (self-hosted LLMs, MITx Supply Chain) suggests these would be trivial to acquire.

[ANALYSIS_REPORT] The candidate is a senior-level Backend Architect and Python developer, showing strong aptitude for system design and automation ('Fast Learner'). However, the role is specifically for a Node.js developer with niche experience in Video/HLS. While the candidate shares the 'Backend' domain, the specific language (Node.js) and streaming technology (HLS) are completely absent from the resume.

[ANALYSIS_REPORT] Strong match for the 'AI Transformation' and strategic leadership aspects; the candidate's self-hosted LLM and 'metal-up' infrastructure experience is a high-value fit for the role's core mission. However, a significant technical stack divergence exists: the role requires a Microsoft/Web stack (C#, React, Azure) while the candidate is Python/Linux/AWS focused. Due to 'Fast Learner' traits, the Cloud/DevOps gaps (Azure, Kubernetes) are minor, but the core language mismatch (C# vs Python) is the primary friction point for a Solution Architect role.

[ANALYSIS_REPORT] The candidate is a highly capable technical architect with strong SQL and logic skills, demonstrating a 'Fast Learner' profile suitable for mastering new tools. However, the role is a deep expert position strictly requiring 7+ years of legacy Microsoft Access development, a technology completely absent from the candidate's modern Cloud/AI/Python stack.

[ANALYSIS_REPORT] Complete domain mismatch. The position requires a Civil Engineer specializing in infrastructure construction (roads, drainage, earthworks) with specific CAD/BIM tools. The candidate is a Software/Systems Architect with a background in Mechatronics and Supply Chain. The hard skills (Civil 3D, DNIT standards, Civil Engineering degree) are non-transferable from the candidate's tech stack.

[ANALYSIS_REPORT] Strong match for the primary Python and Infrastructure (Terraform, Docker) requirements. The candidate's background in automation and 'metal-up' architecture aligns well with the engineering needs. However, the role requires maintenance of legacy/alternative stacks (Java, .NetCore) which are absent from the resume. His 'Fast Learner' profile (self-hosted LLMs, algorithmic trading) mitigates the AWS specific gaps (EKS, Glue), suggesting he can bridge the tool-specific deltas quickly.

[ANALYSIS_REPORT] Exceptional match for the specific 'Open Weights' and 'Self-hosted LLM' requirements, which aligns perfectly with the candidate's recent projects. The candidate's 'Founder' experience satisfies the 'Product Manager' responsibilities. The only explicit keyword gaps are specific Python API web frameworks (e.g., FastAPI, Flask), but the candidate's strong Python automation and Systems Architecture background suggests this is a trivial gap to bridge.

[ANALYSIS_REPORT] The candidate has a strong background in Systems Integration (SSO, APIs), Risk Management (Finance/Supply Chain), and English fluency, which aligns well with the consulting profile. However, the role strictly requires 2+ years of hands-on experience with the **OneTrust** platform and specific Privacy Regulations (GDPR/LGPD), which are major hard skill gaps despite the candidate's 'Fast Learner' ability.

[ANALYSIS_REPORT] Candidate is a strong Infrastructure/Automation engineer but has significant gaps in the specific stack requested. The role requires 'Mobile CI/CD' (App Center, Bitrise) and 'NodeJS', whereas the candidate is heavily focused on Python and general backend/AI infrastructure. While Terraform and AWS align, the specific tooling (Jenkins, Dynatrace) and the Mobile DevOps focus are missing.

[ANALYSIS_REPORT] Major Tech Stack Mismatch. The candidate is a strong Python/AI Automator, whereas the role strictly requires a Microsoft stack specialist (Dynamics 365, X++, C#, .NET). While the candidate has relevant domain knowledge (ERP usage, Supply Chain, Finance), they lack the specific 5+ years of hard technical skills in the required ecosystem.

[ANALYSIS_REPORT] Strong match due to the role's heavy emphasis on 'AI-driven automation' and 'intelligent systems,' which aligns perfectly with the candidate's expertise in self-hosted LLMs and Python automation. While the candidate lacks specific QA tooling experience (Playwright), their engineering background and 'Fast Learner' trait make this a trivial gap to close, especially given the strategic architectural nature of the role.

[ANALYSIS_REPORT] The candidate is a highly capable Systems Engineer and Architect with a strong background in Linux, Automation, and AI infrastructure. However, the role is strictly focused on the Microsoft Enterprise ecosystem (M365, Intune, Windows Server), which represents a distinct stack from the candidate's Python/Linux/AWS experience. While the candidate matches on Identity concepts (SSO/SAML) and general systems engineering principles (documentation, infrastructure), the lack of specific hands-on experience with the Microsoft administration suite is a significant gap, though his fast-learning ability partially mitigates this risk.

[ANALYSIS_REPORT] Strong match for Python and core LLM requirements, with self-hosting experience demonstrating deep technical aptitude ('Fast Learner'). The candidate's 'AWS Basics' and local cluster experience are adjacent to the specific AWS AI services required, making them easily learnable. The primary gap is explicit experience with non-text modalities (Audio/Video), as the resume focuses heavily on Text (LLMs) and Data structures.

[ANALYSIS_REPORT] Strong foundational match. The candidate demonstrates Senior-level capability in Data Modeling and Automation via complex custom systems (Algorithmic Trading, JIT Inventory). His transition to self-hosted AI infrastructure confirms the 'Fast Learner' trait required by the JD. However, strictly as a 'Senior Data Engineer', he lacks explicit experience with standard enterprise Big Data orchestration and streaming tools (Airflow, Kafka, Spark/EMR), having relied on custom Python/SQL solutions instead. He fits the 'Avid Learner' profile perfectly but would need to ramp up on the specific stack.

[ANALYSIS_REPORT] The candidate exhibits a strong 'SRE mindset' through automation (Python), IaC (Terraform), and proven ability to architect resilient self-hosted systems ('Fast Learner'). However, for a 'Staff' level role, the explicit lack of production Kubernetes experience, deep enterprise Cloud knowledge (listing only 'AWS Basics'), and standard Observability tooling (Prometheus/Grafana) are significant gaps. He has the foundational skills to adapt, but lacks the specific toolchain mastery required for immediate Staff-level leadership.

[ANALYSIS_REPORT] Major domain mismatch. The role is a Senior/Lead Frontend Engineering position requiring deep expertise in React and the browser ecosystem. The candidate is a Backend/Infrastructure Architect with no mention of Javascript, Frontend, or UI development in their history. While they possess the 'nice-to-have' Infrastructure skills (Terraform, CI/CD), they lack the mandatory core technical stack.

[ANALYSIS_REPORT] Fundamental domain mismatch. The candidate is a Backend/AI Architect with strong Python and Infrastructure skills, while the role strictly requires a Mid-level Salesforce Specialist. The candidate lacks all primary hard skills (Apex, LWC, Salesforce Ecosystem) which are proprietary and distinct from general backend engineering. While a fast learner, the requirement for 2-3 years of specific platform experience makes this a 'non-starter' match.

[ANALYSIS_REPORT] Candidate fits the 'Business Acumen' and 'Project Management' criteria well through their Founder and Analyst roles. However, the role explicitly requires 2+ years of specific 'CRM consulting' or Product Management experience. The candidate's primary domain is AI Infrastructure, Supply Chain, and ERP, which is adjacent but distinct from the sales/marketing focus of CRM. Strong potential to pivot due to 'Fast Learner' traits, but lacks the core hard skill of CRM expertise.

[ANALYSIS_REPORT] While the candidate's Mechatronics degree provides a relevant theoretical foundation for embedded systems, there is a significant gap in recent, practical application of Automotive protocols (CAN, UDS) and the specific required tech stack (C#/.NET). The candidate is a strong generalist and automation expert, but this role requires specialized, low-level diagnostics and firmware analysis experience that is not present in the professional history.

[ANALYSIS_REPORT] Candidate possesses strong foundational infrastructure knowledge ('Metal-up', Local AI Clusters, Docker) and demonstrated rapid learning ability suitable for Ops roles. However, the role strictly requires specific enterprise virtualization suites (VMware, XenServer, Huawei DCS) which are not present in the resume. The candidate is a strong fit for Modern DevOps/AI but a partial match for legacy Hypervisor Administration.

[ANALYSIS_REPORT] The candidate is a technical 'builder' (Architect/Founder) rather than a process-oriented Project Manager. While the Engineering degree and AI expertise are strong matches, the resume completely lacks the strictly required Agile certifications (CSM) and specific Project Management tooling experience (Jira/Atlassian) demanded by the role.

[ANALYSIS_REPORT] The candidate is a strong Python engineer and Systems Architect with proven 'figure it out' capability (LLMs, Trading Bots), making the transition to Web Scraping highly feasible. However, the resume lacks explicit experience with the specific scraping domain (Scrapy, anti-bot mechanisms, headless browsers) and JavaScript, which are core requirements for this specific support role.

[ANALYSIS_REPORT] The candidate has strong overlaps in Data/Backend logic (Python, SQL, Pipeline Orchestration) and domain relevance (Finance/Supply Chain). However, the role is explicitly 'Full-stack' requiring Node.js and Angular, neither of which are present in the resume. While the candidate's 'Fast Learner' profile suggests they could adapt, the lack of any web frontend framework experience is a significant gap for this specific role.

[ANALYSIS_REPORT] Strong match for the specific AI/LLM requirements, backed by a proven track record of self-hosting and optimizing models (Fast Learner trait). However, a significant gap exists in core web application frameworks; the resume emphasizes Python for automation, data, and infrastructure rather than the requested 'Django' web development or 'Multi-tenant SaaS' architecture experience.

[ANALYSIS_REPORT] The candidate is a highly capable Systems Architect and automation expert with a strong 'Fast Learner' profile (self-hosted AI, algo trading). However, this is a Senior Security Operations (SOC) role. The resume lacks specific experience in core SOC domains: Incident Response, Threat Intelligence, and SIEM tools. While the candidate has strong automation (Python) and general infrastructure skills, the gap between 'AWS Basics' and the required 'Strong experience' for a Senior Cloud Security role is significant. He would likely excel in DevSecOps but lacks the specialized compliance and threat-hunting background for this specific position.

[ANALYSIS_REPORT] The candidate is a highly experienced Senior Engineer/Architect with strong Backend and Data logic skills (Python, SQL), which aligns with the 'Backend' domain. However, the role explicitly requires '1+ years of experience in Java', which is completely absent from the resume. While his OOP knowledge (via Python) and general engineering maturity are strong positives that would allow him to learn quickly (Fast Learner), he currently lacks the primary hard skill required for this specific language-focused role.