Padmi

Data Science Intern

IndiaPosted 5 months ago
Data Science And StatisticsInternFull Time
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Data Science Intern (Paid) Company: Dexter's Tech Location: Remote Duration: 3 Months Opportunity & Benefits Performance-based stipend up to 7,499 Swags and goodies Internship Certificate Letter of Recommendation (based on performance) Potential full-time role based on performance Hands-on experience with real-world data science projects About Dexter's Tech Dexter's Tech empowers aspiring data professionals by providing practical, industry-relevant experience in data science. The internship focuses on building strong foundations in analytics, statistics, and machine learning through live projects aligned with real-world business and technology challenges. Roles & Responsibilities Collect, preprocess, and analyze large datasets Perform Exploratory Data Analysis (EDA) to uncover meaningful insights Build predictive models and machine learning algorithms Create data visualizations and dashboards for effective storytelling Collaborate with cross-functional teams to deliver data-driven solutions Requirements Currently enrolled in or graduated from Data Science, Computer Science, Statistics, or related fields Proficiency in Python or R for data analysis and modeling Familiarity with scikit-learn, TensorFlow, or PyTorch (preferred) Experience with visualization tools such as Tableau, Power BI, or Matplotlib Strong analytical, problem-solving, and communication skills What You Will Gain Real-world exposure to data science workflows Performance-based stipend up to 7,499 Swags and goodies Internship Certificate upon completion Letter of Recommendation based on performance Opportunity to build a strong data science portfolio Potential full-time role based on performance How to Apply Submit your resume and cover letter with the subject line: Data Science Intern Application Application Deadline: 13th January 2026 Equal Opportunity Statement Dexter's Tech is an equal opportunity organization and encourages applications from candidates of all backgrounds.

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