Big Data Analytics Intern

Job Description

Position: Remote Big Data Analytics Intern
Company: PulseForge Labs

About the Role

PulseForge Labs is seeking a detail-oriented and data-driven Big Data Analytics Intern to join our data science team. In this role, you will work with vast datasets to generate insights that drive strategic decision-making and innovation. This internship is ideal for students and recent graduates eager to build a career in big data and analytics, working in a fast-paced environment with industry-leading tools and experts.

Key Responsibilities

• Collect, process, and analyze large datasets from various sources to uncover patterns and trends.
• Use big data tools and techniques, including Hadoop and Spark, to manage and manipulate data at scale.
• Assist in developing and optimizing data models to support analytics and machine learning initiatives.
• Generate visualizations and reports that present data findings clearly to both technical and non-technical stakeholders.
• Collaborate with data science and engineering teams to enhance data collection and storage processes.
• Perform data quality assessments and ensure data accuracy for analytics initiatives.

Qualifications

• Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, or a related field.
• Foundational knowledge of big data tools and platforms, such as Hadoop, Spark, or Hive.
• Proficiency in data analysis using Python, R, or SQL.
• Familiarity with data visualization tools like Tableau, Power BI, or Matplotlib.
• Strong analytical and problem-solving skills, with attention to detail.
• Excellent communication skills for sharing data insights with diverse teams.

Benefits

• Real-world experience working with large datasets and cutting-edge analytics tools.
• Flexible remote work setup and adaptable working hours.
• Mentorship from experienced data scientists and analysts.
• Networking opportunities within the data science and analytics industry.
• Certificate of completion and potential for full-time employment based on performance.
• Access to data science training resources to further enhance technical skills.