Data Science - Internship (Part Time)

About the internship:Selected intern's day-to-day responsibilities include:

A. Data collection & cleaning:

1. Gather data from internal databases, APIs, or public datasets.

2. Identify and handle missing values, inconsistencies, and errors.

3. Transform raw data into a usable format for analysis.

B. Data exploration & analysis:

1. Perform exploratory data analysis (EDA) to understand patterns and trends.

2. Use statistical methods to identify correlations, anomalies, or outliers.

3. Visualize data using charts, graphs, and dashboards (Matplotlib, Seaborn, Tableau, etc.).

C. Feature engineering & preprocessing:

1. Create new features from existing data to improve model performance.

2. Normalize, encode, or scale data as needed.

3. Handle categorical and time-series data preprocessing.

D. Modeling & machine learning:

1. Assist in building predictive or classification models using Python/R.

2. Test multiple algorithms and evaluate performance using metrics like accuracy, F1-score, RMSE, etc.

3. Fine-tune hyperparameters and document findings.

E. Reporting & documentation:

1. Prepare reports summarizing insights, trends, and model results.

2. Maintain clear documentation for code, methodology, and workflows.

3. Present findings to the team or mentor in meetings.Who can apply:Only those candidates can apply who:are available for the part time job/internshipcan start the part time job/internship between 19th Sep'26 and 24th Oct'26are available for duration of 2 monthsare from Erode onlyhave relevant skills and interests* Women wanting to start/restart their career can also apply.* Freshers looking for jobs may also applyStipend:INR₹ 7,000 - 25,000 /monthDeadline:[hidden]:59:59Other perks:Certificate, Letter of recommendation, Flexible work hours, Job offerSkills required:Python, SQL, Data Analytics, Machine Learning, Data Science, Natural Language Processing (NLP), Deep Learning and Artificial intelligenceOther Requirements:1. Those who are pursuing engineering and management departments, student coordinator, event coordinator, and placement coordinator are welcome to apply.About Company:Innoknowvex is a cutting-edge edtech platform designed to seamlessly connect students with internships, professional training, career development, and expert mentorship. Our mission is to bridge the gap between academic education and industry requirements by providing students with access to industry-relevant programs, hands-on training, and specialized mentorship. Through a structured, expert-driven approach, we empower aspiring professionals with the practical skills and industry insights necessary to excel in their chosen fields.Additional information:

Stipend Structure:

Fixed pay: ₹ 5,000 - 20,000 /month

Incentive pay: ₹ 2,000 - 5,000 /month

Job offer: On successful conversion to a permanent employee, the candidate can expect a salary of ₹ 400000 to 700000/year

Responsibilities

Selected intern's day-to-day responsibilities include:

A. Data collection & cleaning:

1. Gather data from internal databases, APIs, or public datasets.

2. Identify and handle missing values, inconsistencies, and errors.

3. Transform raw data into a usable format for analysis.

B. Data exploration & analysis:

1. Perform exploratory data analysis (EDA) to understand patterns and trends.

2. Use statistical methods to identify correlations, anomalies, or outliers.

3. Visualize data using charts, graphs, and dashboards (Matplotlib, Seaborn, Tableau, etc.).

C. Feature engineering & preprocessing:

1. Create new features from existing data to improve model performance.

2. Normalize, encode, or scale data as needed.

3. Handle categorical and time-series data preprocessing.

D. Modeling & machine learning:

1. Assist in building predictive or classification models using Python/R.

2. Test multiple algorithms and evaluate performance using metrics like accuracy, F1-score, RMSE, etc.

3. Fine-tune hyperparameters and document findings.

E. Reporting & documentation:

1. Prepare reports summarizing insights, trends, and model results.

2. Maintain clear documentation for code, methodology, and workflows.

3. Present findings to the team or mentor in meetings.