Data Science Intern (Customer Success) - Cresta Remote
1 day ago⚠️ Before applying, please carefully review all the job requirements
- Location:
- United States
- Work Arrangement:
- Remote
- Experience:
- Enrolled in a Bachelor’s or Master’s degree program in Computer Science, Engineering, or a related field
- Job Type:
- Internship
- Company:
- Cresta
- Salary:
- Negotiable
- Posted:
- 2026-09-13
Job Overview
- Cresta is seeking a Data Science Intern to join its Customer Success team in a fully remote capacity within the United States. Cresta develops artificial intelligence solutions for contact centers, combining conversational AI agents, real-time human agent support, and conversation intelligence to enhance enterprise customer experiences.
- In this role, the intern collaborates with data scientists, software engineers, and business stakeholders to analyze real-world conversation datasets and support data-driven decision-making. Daily responsibilities include collecting, cleaning, and preprocessing structured and unstructured data, conducting exploratory data analysis, constructing machine learning models, and designing visual dashboards. Additionally, the intern assists with model deployment, performance monitoring, and process documentation.
Key Responsibilities
- ★ Gather, clean, and preprocess structured and unstructured datasets for analytical processing.
- ★ Perform exploratory data analysis to identify key operational patterns and technical insights.
- ★ Construct, evaluate, and refine machine learning models under technical guidance.
- ★ Build data visualizations and analytical dashboards to communicate findings to stakeholders.
- ★ Support the deployment of machine learning models and track their ongoing performance.
- ★ Process and manage large datasets using Python, SQL, and cloud infrastructure platforms.
- ★ Document experimental methods, code repositories, and analytical outcomes clearly.
- ★ Participate in team technical demos, feedback sessions, and ongoing learning activities.
Required Skills and Qualifications
- ★ Current enrollment in a Bachelor’s or Master’s degree program in Computer Science, Engineering, or a related field.
- ★ Practical coding experience in Python or another general-purpose programming language.
- ★ Foundational knowledge of statistical concepts and core machine learning principles.
- ★ Familiarity with data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- ★ Experience writing SQL queries and interacting with relational database systems.
- ★ Strong analytical, quantitative, and technical problem-solving abilities.
- ★ Solid communication skills and readiness to collaborate with internal teams and customers.
- ★ Demonstrated interest in artificial intelligence, machine learning, and software engineering.
- ★ Preferred exposure to data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn.
- ★ Optional familiarity with cloud platforms (AWS, GCP, Azure), version control with Git, or big data tools like Spark or Hadoop.
Who May Be a Good Fit for This Role?This role may be suitable for undergraduate or graduate students pursuing degrees in Computer Science or Engineering who wish to gain practical data science experience within the artificial intelligence sector. Candidates who have developed a solid foundation in Python, database querying with SQL, and core machine learning principles through coursework or personal projects will find this opportunity well matched to their background. It is ideal for analytical individuals seeking a remote internship in the United States that offers direct mentorship from senior data scientists while addressing customer-facing technical challenges.
Application TipsApplicants may want to highlight relevant academic coursework, personal research, or technical projects involving Python, SQL, and machine learning libraries like Pandas or Scikit-learn on their resume. Including details about experience with data visualization tools, cloud infrastructure platforms, or version control tools like Git can further demonstrate technical readiness. Candidates should ensure their application clearly reflects current enrollment in a Bachelor's or Master's degree program in Computer Science or Engineering. Demonstrating an active interest in artificial intelligence and collaborative problem-solving will also support a well-rounded application.
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