Suraj Rajolad
MES Data Analyst
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Job Compatibility Score
MES Data Analyst
35%Here is the completed Candidate Evaluation Table for Suraj Rajolad, based on the provided Job Description and Resume.
Total Score: 35 / 100
Key Insights: This candidate is a strong Data Analyst with solid SQL and Python skills, but he is not a fit for this specific role. The JD is for a Manufacturing Execution Systems (MES) Analyst in a semiconductor/electronics environment. Suraj has zero experience in manufacturing, MES systems, or the semiconductor domain. His experience is in HR systems (Workday), EdTech, and banking chatbots. While his SQL is strong, the lack of domain and tool relevance makes this a low-match profile. He would be a great candidate for a general Data Analyst role, but not this one.
📊 Candidate Evaluation Table
| Category | Details from Job Description | Claimed Experience | Relevant Experience | Evidence from Resume | Score |
|---|---|---|---|---|---|
| Job Titles | MES Analyst / Data Analyst (MES focus) | 4+ years as Data Analyst | 0 years | "Data Analyst" at ChiEAC and UMass, but no MES or manufacturing context. Last relevant title was "Workday Analyst" (HR, not MES). | 0/15 |
| Primary Role-Based Skills | Advanced SQL (joins, CTEs, window functions, aggregations) | SQL listed as a skill | 4+ years | SQL used extensively: "Created SQL-based validation layers," "Developed end-to-end SQL-based ETL pipelines," "SQL-based deduplication processes" at WIPRO. | 15/20 |
| Data validation & quality checks | Claimed via "improving data integrity by 30%" | 4+ years | "Created SQL-based validation layers within ETL pipelines, ensuring data integrity," "Developed end-to-end SQL-based ETL pipelines with data validation checks." | ||
| Root-cause analysis for data discrepancies | Not explicitly claimed | 2 years (at WIPRO) | "Improved system reliability... by analyzing Service Cloud trends... reducing incidents by 30%." This is close, but not specific to MES data. | ||
| Large dataset analysis (trends, process improvement) | Claimed via "analyze large datasets" | 4+ years | "Analyze large datasets to identify issues, trends" is a generic claim. Evidence is in "Wage Prediction" and "SpaceX" projects, but not in a professional MES context. | ||
| MES-specific data knowledge | Not mentioned | 0 years | No mention of MES, shop floor data, or manufacturing datasets anywhere in the resume. | ||
| Secondary Skills | Python (for data analysis/automation) | Listed as a primary skill | 4+ years | "Built AI-powered... solutions using Python," "Developed end-to-end data pipelines using Python." Strong evidence. | 5/10 |
| ETL pipeline development | Claimed via "automated ETL workflows" | 4+ years | "Developed end-to-end SQL-based ETL pipelines," "Built automated ETL workflows to improve data quality." Good evidence. | ||
| Data visualization (for insights) | Power BI, Tableau, Matplotlib, Seaborn | 4+ years | "Creating analytical visualizations using ggplot2," "Leveraging Tableau and seaborn." Solid, but not the core need. | ||
| Tools & Platforms | MES Systems (e.g., Siemens, Rockwell, SAP ME) | Not mentioned | 0 years | No MES tools listed. | 0/10 |
| SQL Databases (e.g., SQL Server, PostgreSQL) | SQL Server, PostgreSQL listed | 4+ years | "SQL, MySQL, MongoDB, Redshift, Microsoft SQL Server, PostgreSQL." Strong database tool knowledge. | ||
| Certifications | None explicitly required in JD | N/A | N/A | Holds "Big Data, IBM Data Science" and "Cyber Security & Ethical Hacking" certifications. Not directly relevant to MES. | 0/5 |
| Experience Level | Mid-level (3-5 years implied) | 4+ years | 4+ years | "Data Analyst with 4+ years of experience." Matches the level, but in the wrong domain. | 5/10 |
| Domain Expertise | Electronics / Semiconductor manufacturing | Not mentioned | 0 years | Last 3 domains: EdTech (ChiEAC), Banking/Finance (UMass chatbot), HR/Tech (WIPRO/Meta). No manufacturing or semiconductor experience. | 0/10 |
| Consistency Across Summary, Experience, and Education | N/A | N/A | N/A | Summary claims "Data Analyst with 4+ years," which is consistent with experience. Education (MS Data Science) aligns with the analytical nature of the role, but not the domain. | 10/10 |