Data Science Internship in Mumbai at International Institute Of Data Science & Technology
Data Science
International Institute Of Data Science & TechnologyLocation(s): Mumbai (Hybrid)DESCRIPTION
About the internship
A. Data collection & cleaning:
1. Assist in sourcing, cleaning, and preprocessing data from diverse platforms to ensure accuracy and usability
2. Detect and resolve inconsistencies, missing values, and anomalies in datasets
B. Exploratory Data Analysis (EDA):
1. Perform exploratory analyses to identify key trends, patterns, and relationships within the data
2. Leverage visualizations to interpret findings and effectively communicate insights to the team
C. Model development & testing:
1. Support the end-to-end development of machine learning models, including data preparation, feature engineering, and performance evaluation
2. Gain hands-on experience with supervised and unsupervised learning techniques under mentorship
D. Data visualization & reporting:
1. Design and develop dashboards and reports to showcase analytical insights and model performance metrics
2. Utilize tools such as Python (e.g., Matplotlib, Seaborn) or Power BI to build compelling visualizations
E. Collaboration & documentation:
1. Work closely with cross-functional teams to ensure data initiatives are aligned with business objectives
2. Maintain thorough documentation of data workflows, analysis processes, and model outcomes
Skill(s) required
Who can apply
Only those candidates can apply who:
1. are available for full time (in-office) internship
2. can start the internship between 8th Jul'25 and 12th Aug'25
3. are available for duration of 6 months
4. have relevant skills and interests
Other requirements
A. Education:
1. Pursuing or completing a degree in computer science, data science, statistics, mathematics, or a related field
B. Technical proficiency:
1. Strong foundation in Python (preferred libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn)
2. Basic understanding of machine learning concepts (supervised and unsupervised)
3. Familiarity with data querying using SQL is a plus
C. Analytical mindset:
1. Ability to approach problems methodically and draw actionable insights from data
2. Comfort in working with large datasets and identifying patterns or anomalies
D. Tools knowledge:
1. Exposure to data visualization tools (e.g., Power BI, Tableau, or Python-based tools)
2. Experience using Jupyter Notebooks, Google Colab, or similar platforms
3. Familiarity with Git/GitHub for version control
E. Communication & collaboration:
1. Strong written and verbal communication skills
2. Ability to present data insights in a clear, concise manner to both technical and non-technical audiences
3. Team-oriented, proactive, and receptive to feedback
F. Preferred traits:
1. Quick learner with a curiosity for data and a passion for solving real-world problems
2. Prior internship or project experience in data analysis or machine learning is a bonus
3. Exposure to cloud platforms (AWS, GCP) or model deployment tools is an added advantage