Data Science Engineer Intern

This is a full-time internship for a duration of 3 months. Please note that this is an unpaid internship; however, based on performance, candidates may be offered a paid contract role upon successful completion of the internship. High Potential for Permanent Role: Top performers will have a strong opportunity to transition into a full-time permanent position.

• Data Analysis and Exploration
  




• Analyze large, complex datasets to identify trends, patterns, and relationships.
  


• Conduct exploratory data analysis (EDA) to gain insights and formulate hypotheses.
  


• Utilize statistical methods and data visualization techniques to communicate findings effectively.
  




• Predictive Modeling and Machine Learning
     o   Experience and knowledge in analyzing and developing forecasting models using time series data
  




• Develop predictive models using machine learning algorithms.
  


• Perform feature engineering, model selection, and hyper-parameter tuning to optimize model performance.
  


• Ensure that model always meet the relevant evaluation metrics.
  




• Data Mining and Pattern Recognition
  




• Apply data mining techniques to extract actionable insights from structured and unstructured data.
  


• Identify patterns and anomalies in data to detect fraud, predict customer behavior, or optimize business processes.
  


• Implement clustering, classification, regression, and other machine learning algorithms as needed.
  




• Collaboration and Communication
  




• Excellent story telling and presentation skills 
  


• Collaborate with cross-functional teams, including engineers, product managers, and business stakeholders.
  


• Translate technical findings into actionable insights and recommendations for non-technical audiences.
  


• Present findings and proposals in clear, concise, and compelling ways.
  

Requirements

Benefits

• Opportunities for high-speed professional growth and development.
  


• Collaborative and supportive work environment.
  


• Training (Technical & Soft skills)