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Data Engineer with less than a year in AI and Data Science projects.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
To build a successful career in Artificial Intelligence and Data Science by applying my technical knowledge, analytical skills, and practical experience while continuously learning and contributing to innovative projects.
York St John University
MSc Data Science · Data Science
August 1, 2025 – June 30, 2026
St. Mary's Group of Institutions
Bachelor of Technology · Electronics and Communication Engineering
August 1, 2019 – June 30, 2023
Vidwan Junior College
Intermediate (MPC)
June 1, 2017 – May 31, 2019
Kerala E.M High School
SSC
June 1, 2017 – May 31, 2017
Randstad Digital Private Limited (Deputed to NVIDIA Graphics Private Limited)
Associate Process Executive-Data Engineer
October 1, 2024 – July 1, 2025
Pune, Maharashtra, India
AI Data Collection Projects
June 19, 2026 – Present
Worked on AI data collection and dataset preparation projects for machine learning model training. Assisted in collecting and organizing datasets for AI model training. Ensured data accuracy and consistency in annotation and processing tasks.
Accident Detection and Avoidance Robot
June 19, 2026 – Present
Developed an obstacle-avoiding robotic system using ultrasonic sensors. Designed to detect obstacles and avoid collisions automatically.
A Prototypic Weather Monitoring Satellite
June 19, 2026 – Present
Developed a prototype system to monitor atmospheric conditions such as temperature, pressure, and gas levels. Integrated IoT components for environmental monitoring.
Cultural Fit Analysis
The candidate's academic projects demonstrate an interest in diverse technical areas, including robotics and IoT, alongside AI data collection. The ongoing MSc in Data Science aligns well with a continuous learning culture. The experience at Randstad Digital (deputed to NVIDIA) shows exposure to a corporate environment, and the listed soft skills suggest a collaborative mindset. However, the limited professional experience and lack of diverse project technologies beyond basic Python and AI data collection might indicate a need for broader exposure to different data engineering paradigms and tools to fully integrate into a diverse technical team.
Soft Skills & Operational Fit
The candidate highlights strengths such as being a quick learner, strong attention to detail, team-oriented, adaptable, motivated, and analytical. These traits suggest a good operational fit for roles requiring meticulous data handling and collaborative problem-solving. The experience in automating workflows and ensuring data quality indicates a proactive approach to efficiency and reliability.