Data Science Internship 🎓

We are seeking a Data Science Intern pursuing a master’s degree in Data Analytics or a related field to join our dynamic team. The ideal candidate has a strong interest in the retail and apparel space, coupled with foundational experience in Microsoft’s Azure platform. This internship offers hands-on opportunities to analyze complex datasets, develop predictive models, and drive actionable insights that impact business decisions.

KEY RESPONSIBILITIES:

• Collaborate with the data science team to design, develop, and implement data-driven solutions tailored to the retail and apparel industry.
• Conduct exploratory data analysis (EDA) to uncover patterns and trends in customer behavior, sales performance, and inventory management.
• Build and refine predictive models and machine learning algorithms to enhance business outcomes, such as demand forecasting and personalized marketing strategies.
• Assist in the integration and management of data pipelines using Microsoft Azure tools, including Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
• Present findings and recommendations through clear visualizations and reports using Power BI or similar tools.
• Participate in cross-functional projects to align data science initiatives with broader business goals.

QUALIFICATIONS:

• Demonstrated interest in the retail and apparel industry, with knowledge of market trends or consumer behavior.
• Hands-on experience with Microsoft Azure services, such as Azure ML, Azure Data Factory, or Azure Synapse Analytics.
• Proficiency in programming languages such as Python or R, and experience with libraries like pandas, scikit-learn, or TensorFlow.
• Familiarity with SQL for querying and managing databases.
• Basic knowledge of data visualization tools such as Power BI, Tableau, or Matplotlib.
• Strong analytical, problem-solving, and communication skills.

DESIRED EDUCATION AND EXPERIENCE:

• Currently pursuing a Master’s degree in Data Analytics, Data Science, Statistics, Computer Science, or a related field.
• Experience with retail datasets, such as point-of-sale (POS) data, inventory systems, or customer segmentation.
• Exposure to cloud-based machine learning workflows or model deployment on Azure.
• Understanding of A/B testing and other statistical evaluation methods.