Data Science Intern

Job Description

Our team is looking for candidates with exceptional technical aptitude, a passion for applied data science, and an interest in telling stories through data to solve real-world business problems.

Responsibilities:

• Collaborate proactively with various team members to propose solutions and design innovative solutions to optimize processes and promote informed decision-making for clients.
• Develop POCs, including work on challenging and research-based initiatives using advanced machine learning methods focusing on tangible outcomes.
• Prepare insights using large and various types of data (structured/non-structured).
• Implement machine learning models, data mining methods, and statistical analysis.
• Leverage visualization tools/packages to create powerful representations of results.
• Produce data-driven insights to help in informed decisions and actions by telling a convincing story and effectively communicating findings to business partners and executives.
• Collaborate with the DevOps team to deploy production-scale solutions.
• Quickly learn new methods, tools, and technologies presented in research communities to implement and adapt.

Requirements:

• We are open to recent Undergraduates, who have an academic focus in Computer Science, Operations Research, Statistics, Econometrics, or a related technical field.
• Must have demonstrated familiarity or interest in machine learning, statistical analysis, or data mining through previous internships, personal/ academic projects, hackathons, and/or publications.
• Hands-on experience with real datasets and familiarity using Python, sklearn, numpy, pandas, and SQL.
• Familiarity with various machine learning techniques and statistical methodologies (Bayesian methods, experimental design, causal inference).
• A portfolio of sample projects or a git repo to showcase projects worked on and/or producing academic papers.

Job Types: Full-time, Internship
Contract length: 3 months

Pay: Rs50,000.00 per month

Education:

• Bachelor's (Required)