Data Science Intern (Customer Success)

Summary

Cresta is a company focused on enhancing customer experiences through AI technology. They are seeking a Data Science Intern to gain hands-on experience in data analysis, model building, and supporting data-driven decision-making while collaborating with various teams.

Responsibilities

• Collect, clean, and preprocess structured and unstructured data
• Perform exploratory data analysis to identify trends and insights
• Build and evaluate machine learning models under guidance
• Develop data visualizations and dashboards to communicate findings
• Assist in deploying models and monitoring their performance
• Work with large datasets using tools like Python, SQL, and cloud platforms
• Document processes, experiments, and results clearly
• Participate in team demos, feedback sessions, and learning opportunities

Skills

• Enrolled in a Bachelor's or Master's degree program in Computer Science, Engineering, or a related field
• Experience writing code in Python (or another general-purpose language)
• Strong interest in artificial intelligence, machine learning, or software engineering
• Basic understanding of statistics and machine learning concepts
• Familiarity with libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow/PyTorch
• Experience with SQL and working with databases
• Strong analytical and problem-solving skills
• Excellent communication skills and willingness to collaborate with teammates and customers
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
• Familiarity with cloud platforms (AWS, Google Cloud Platform, or Azure)
• Knowledge of version control (Git)
• Exposure to big data tools (Spark, Hadoop) is a plus

Qualifications

Must Haves

• Enrolled in a Bachelor's or Master's degree program in Computer Science, Engineering, or a related field
• Experience writing code in Python (or another general-purpose language)
• Strong interest in artificial intelligence, machine learning, or software engineering
• Basic understanding of statistics and machine learning concepts
• Familiarity with libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow/PyTorch
• Experience with SQL and working with databases
• Strong analytical and problem-solving skills
• Excellent communication skills and willingness to collaborate with teammates and customers

Nice to Haves

• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
• Familiarity with cloud platforms (AWS, Google Cloud Platform, or Azure)
• Knowledge of version control (Git)
• Exposure to big data tools (Spark, Hadoop) is a plus