Data Science Intern

Company Description Codevlux Software is a technology company focused on building data-driven software solutions for clients across diverse industries. The organization values innovation, practical problem-solving, and collaboration between engineering and analytics teams. As part of its growth, Codevlux Software invests in emerging talent and offers opportunities to work with modern data tools and methodologies. Interns can expect a culture that encourages learning, mentorship, and experimentation with real-world datasets. The company aims to help team members develop strong technical foundations and professional skills in a supportive environment.
Role Description This Data Science Intern role is a hybrid internship based in Bengaluru, with a mix of on-site collaboration and work-from-home flexibility. Interns will assist in collecting, cleaning, and preparing data for analysis, and support in building exploratory reports and visualizations. Day-to-day tasks include applying statistical and analytical techniques, contributing to basic predictive models, and helping validate results under the guidance of senior data professionals. The role also involves documenting workflows, sharing findings with team members, and participating in code reviews and team discussions. Interns will work closely with software and data teams to contribute to data-informed product decisions and improvements.
Qualifications
Candidates should possess strong Analytical Skills and a solid foundation in Data Analysis.
Candidates should possess knowledge of Statistics and basic Data Science concepts.
Candidates should possess familiarity with Data Analytics tools or workflows.
Basic experience with programming languages commonly used in data science (such as Python or R) and exposure to libraries for data manipulation and visualization.
Enrollment in or completion of a degree program in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
Ability to interpret data, communicate insights clearly, and collaborate effectively in a team setting.
Interest in learning new tools, frameworks, and best practices in data science and software development.

Work arrangement
Hybrid