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Hir Infotech
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Data Science & Analytics Intern

Data Science & Analytics Intern

Hir Infotech

0 - 1 years

0 Lacs

ahmedabad

Posted:1 day ago| Platform:

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Skills Required

computer science data analysis analytical data collection business strategy forecasting internship operations analytics sql

Work Mode

Work from Office

Job Type

Internship

Job Description

Qualification

AI RD Department

Role Overview

Join our data science team to explore cutting-edge analytics technologies, develop predictive models, and drive data-driven decision making. This collaborative learning opportunity focuses on end-to-end data science workflows, advanced statistical analysis, and real-world AI applications in business contexts.

Key Responsibilities

Conduct comprehensive data collection, cleaning, preprocessing, and exploratory data analysis using Python, R, and SQL frameworks
Develop and implement machine learning models for classification, regression, clustering, and time-series forecasting applications
Create advanced data visualizations and interactive dashboards using Tableau, Power BI, matplotlib, and seaborn libraries
Perform statistical analysis, hypothesis testing, and A/B testing to derive actionable business insights
Build and deploy predictive analytics models to support business strategy and operational optimization
Collaborate with cross-functional teams to translate business requirements into analytical solutions and recommendations
Document analytical processes, create technical reports, and present findings to stakeholders through compelling data storytelling

Required Qualifications

Must-Haves

Bachelor s or Master s degree in Data Science, Statistics, Computer Science, Mathematics, or related field (final year students or recent graduates)
Strong programming proficiency in Python with experience in NumPy, Pandas, Scikit-learn, and Jupyter Notebooks
Solid understanding of statistical concepts including descriptive statistics, probability distributions, and inferential statistics
Knowledge of SQL for database querying and data manipulation from various data sources
Experience with data visualization tools and techniques for creating meaningful insights from complex datasets

Nice-to-Haves

Hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or advanced scikit-learn applications
Familiarity with cloud platforms (AWS, GCP, Azure) for data processing, model deployment, and distributed computing
Knowledge of big data technologies including Spark, Hadoop, or NoSQL databases for large-scale data processing
Experience with advanced analytics techniques including deep learning, NLP, or computer vision applications
Previous internship experience or portfolio projects demonstrating real-world data science problem-solving capabilities

Learning Outcomes and Development

Gain hands-on experience with industry-standard data science methodologies and end-to-end analytics project lifecycle management
Master cutting-edge analytical tools, frameworks, and cloud-based platforms through mentorship from senior data scientists
Develop expertise in translating complex business problems into data-driven solutions with measurable impact
Build comprehensive understanding of AI ethics, bias evaluation, and responsible analytics practices in enterprise environments
Access to real-world datasets and high-visibility projects with potential for significant business impact and career advancement
Enhanced presentation and stakeholder communication skills through regular project demos and cross-functional collaboration

This unpaid internship represents a collaborative knowledge-sharing opportunity in the high-growth field of data science and analytics. Outstanding performers will be considered for full-time positions based on analytical excellence, innovative problem-solving, and demonstrated ability to drive business value through data insights.

Duration:

6 months

Hours:

09:00 AM to 06:00 PM (Monday to Friday)

Location:

Ganesh Glory 11, Jagatpur, Ahmedabad, 382470 (Offline Internship)

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Data Science & Analytics Intern