Dilshad Ali

Bhubaneshwar, Odisha, India

Since February 24, 2026

Skills

HTML5PythonNext.jsMachine LearningGit-GitHubFront-endTensorFlowCSS

Experience

Infosys Springboard

AI/ML Intern

August 1, 2025 – October 1, 2025

GauravGo Gaming Technologies

Game Development Intern

June 1, 2024 – October 1, 2024

Key Strengths

Strong academic background in Computer Science (AI) with a CGPA of 8.3/10, indicating a solid theoretical foundation.
Relevant internship experience in AI/ML at Infosys Springboard, focusing on modular AI pipelines, scalable ML workflows, and data processing optimization.
Hands-on project experience (WellTrack, MarketWatch AI) demonstrating practical application of AI, full-stack development, API design, and performance optimization.
Proficiency in Python, Machine Learning, Deep Learning, Data Analysis, and core concepts like OOP, DSA, and System Design.
Positive communication skills (85% English test) and good cultural fit indicators (77% psychometric test, Agile collaboration).

Skill Analysis

Python Programming & Data Handling

★★★★★

77%

Achieved a solid 77%, indicating good foundational proficiency in Python programming, data analysis, and testing, with some room for advanced skill development.

algorithmsData Analysis with PythonStreaming-DataUnit-TestingPython 3.x

Strengths

Demonstrated solid understanding of core Python 3.x syntax and features.
Proficient in applying algorithmic thinking to problem-solving.
Capable of performing data analysis tasks using Python.
Familiar with unit testing principles for code quality.

Limitations

Potential gaps in advanced Python concepts or complex algorithmic implementations.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's psychometric test score of 77% suggests a good alignment with typical workplace values, including logical reasoning, a positive work attitude, and effective stress handling. Their internship experience explicitly mentions collaboration in Agile teams and cross-functional work, reinforcing a team-oriented mindset and adaptability to structured development environments.

Soft Skills & Operational Fit

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Key Strengths

Strong academic background in Computer Science (AI) with a CGPA of 8.3/10, indicating a solid theoretical foundation.
Relevant internship experience in AI/ML at Infosys Springboard, focusing on modular AI pipelines, scalable ML workflows, and data processing optimization.
Hands-on project experience (WellTrack, MarketWatch AI) demonstrating practical application of AI, full-stack development, API design, and performance optimization.
Proficiency in Python, Machine Learning, Deep Learning, Data Analysis, and core concepts like OOP, DSA, and System Design.
Positive communication skills (85% English test) and good cultural fit indicators (77% psychometric test, Agile collaboration).

Skill Analysis

Python Programming & Data Handling

★★★★★

77%

Achieved a solid 77%, indicating good foundational proficiency in Python programming, data analysis, and testing, with some room for advanced skill development.

algorithmsData Analysis with PythonStreaming-DataUnit-TestingPython 3.x

Strengths

Demonstrated solid understanding of core Python 3.x syntax and features.
Proficient in applying algorithmic thinking to problem-solving.
Capable of performing data analysis tasks using Python.
Familiar with unit testing principles for code quality.

Limitations

Potential gaps in advanced Python concepts or complex algorithmic implementations.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Data Science & Artificial Intelligence Fundamentals

★★★★★

88%

Scored an excellent 88%, reflecting a strong grasp of fundamental Data Science and Artificial Intelligence concepts crucial for an AI Engineer role.

Machine Learning ConceptsAI PrinciplesData InterpretationData Scientist

Strengths

Strong foundational understanding of data science methodologies and AI principles.
Ability to interpret data and apply AI concepts effectively.
Good theoretical knowledge relevant to AI Engineer roles.

Limitations

Minor areas for refinement in specific advanced AI algorithms or complex data modeling techniques.