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Data Analyst with 4+ years in Data Science & Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
As a Data Analyst graduate with strong drive and self motivation, and got trained at Netzwerk Academy as Data Scientist I am dedicated to forging a succesful career. I am looking for a Data Science or Data Analyst role. Also, as a First class undergraduate degree in Computer Science and Engineering and MSc in Data Analytics, I bring energy and ambition to table.
De Montfort University
Master of Science · Data Analytics
August 1, 2022 – June 30, 2023
RKDF Institue Of Science And Technology
Bachelor of Engineering · Computer Science
August 1, 2016 – June 30, 2020
Netzwerk AI
Data Science & Analyst Intern
January 1, 2025 – Present
India
Unified Mentor
Data Analyst Intern
January 1, 2024 – December 31, 2024
India
Bradgate Bakery (United Kingdom)
Production Operator
January 1, 2022 – December 31, 2023
United Kingdom
Data Science
Netzwerk Academy
January 1, 2024 – January 1, 2025
Cultural Fit Analysis
The candidate's academic background in Computer Science and Data Analytics, coupled with internships in data analysis and data science, aligns well with a data-centric organizational culture. Their leadership role as Treasurer at a university society indicates engagement and responsibility beyond academics. The diverse work experience, including a non-technical role, suggests adaptability and a broad perspective, which can contribute positively to team dynamics. However, the limited project diversity in the resume makes it difficult to fully assess breadth of application.
Soft Skills & Operational Fit
The candidate demonstrates problem-solving skills and communication abilities, as evidenced by their project descriptions and leadership experience as Treasurer. Their internship experiences suggest an ability to work within a team and adapt to industry-standard tools. The production operator role, while not directly data-related, indicates an understanding of operational efficiency and quality standards.