Cresta - Data Science Intern (Customer Success)
Requirements
• 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). • Python • 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 • 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, GCP, or Azure) • Knowledge of version control (Git) • Exposure to big data tools (Spark, Hadoop) is a plus • This posting will be used to fill a newly-created role. • We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored. If you are uncertain whether you have been contacted by an official Cresta employee, reach out to [email protected].
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. • This role provides mentorship and exposure to customer-facing technical problem solving in a fast-moving AI/Product environment.
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