Siddharth Sharma

Python / SQL – CrateDB Intern

https://www.opentalent.in/siddharth-sharma

Gwalior, indiaMember since October 8, 2025

Key Strengths

Strong foundational skills in Python, demonstrated through high performance in the Data Scientist assessment and multiple AI/ML projects.
Proficiency in SQL and database concepts (MySQL listed, projects imply data handling).
Practical experience in applying machine learning and deep learning techniques (CNNs, TensorFlow, Scikit-learn) to solve real-world problems.
Experience with embedded systems and IoT integration, showcasing ability to work with hardware and software.
The candidate's intern-level experience and strong Python/SQL foundation align well with the 'Python / SQL – CrateDB Intern' target role, despite lacking specific CrateDB experience.

Skill Analysis

Data Science & Artificial Intelligence

★★★★★

94%

Achieved a very high score, demonstrating strong proficiency in Data Science and AI concepts, further supported by relevant project experience in CNNs, TensorFlow, and model deployment.

Machine LearningDeep LearningCNNTensorFlowPythonWaste ClassificationReal-time DetectionEmbedded SystemsOpenCVRaspberry PiModel Evaluation

Cultural & Operational Fit

Cultural Fit Analysis

The psychometric test score of 65% indicates a moderate cultural fit, suggesting the candidate possesses foundational attributes for teamwork and work ethic but may benefit from development in specific areas such as advanced logical reasoning or stress management. The NGO experience highlights a capacity for collaboration and initiative.

Soft Skills & Operational Fit

The candidate demonstrates moderate soft skills, with a psychometric score of 65% indicating average logical reasoning, work attitude, stress handling, and team collaboration. The English test score of 65% suggests communication clarity and professional language usage are adequate but have room for improvement. Experience as an 'Event Management Head' at an NGO suggests organizational and leadership potential.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Experience

Helping Hut NGO

Event Management Head

November 1, 2024 – August 1, 2025

Gwalior

MITS

Summer Internship Program

June 1, 2023 – July 1, 2023

Gwalior

Key Strengths

Strong foundational skills in Python, demonstrated through high performance in the Data Scientist assessment and multiple AI/ML projects.
Proficiency in SQL and database concepts (MySQL listed, projects imply data handling).
Practical experience in applying machine learning and deep learning techniques (CNNs, TensorFlow, Scikit-learn) to solve real-world problems.
Experience with embedded systems and IoT integration, showcasing ability to work with hardware and software.
The candidate's intern-level experience and strong Python/SQL foundation align well with the 'Python / SQL – CrateDB Intern' target role, despite lacking specific CrateDB experience.

Skill Analysis

Data Science & Artificial Intelligence

★★★★★

94%

Achieved a very high score, demonstrating strong proficiency in Data Science and AI concepts, further supported by relevant project experience in CNNs, TensorFlow, and model deployment.

Machine LearningDeep LearningCNNTensorFlowPythonWaste ClassificationReal-time DetectionEmbedded SystemsOpenCVRaspberry PiModel Evaluation

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Data Engineering (Azure)

★★★★★

45%

The score of 45% suggests a limited understanding of advanced Azure Data Engineering topics, including Databricks DLT, streaming, and cost optimization, indicating a need for significant upskilling in this area.

AzureDatabricksDelta Live Tables (DLT)Data StreamingCost OptimizationCloud Data Platforms

Strengths

Possesses some foundational knowledge in Azure Data Engineering concepts, as indicated by a 45% score.

Limitations

Significant gaps in understanding or practical application of advanced Azure-specific data engineering concepts, including Databricks DLT, streaming, and cost management.
The score suggests a need for substantial development in cloud-native data pipeline design and optimization within the Azure ecosystem.