About this role.
Cresta seeks a full-time remote US Data Science Intern to support customer-success work in a fast-moving AI and product environment. The intern will prepare structured and unstructured data, perform exploratory analysis, build and evaluate machine-learning models under guidance, and create dashboards and visualizations. Core requirements include enrollment in a relevant bachelor’s or master’s program, Python, SQL, statistics and machine-learning fundamentals, and strong communication skills. Experience with Pandas, NumPy, scikit-learn, TensorFlow or PyTorch is preferred, while cloud platforms, Git, visualization tools, and Spark or Hadoop are beneficial. The role provides mentorship and exposure to customer-facing technical problem-solving across data science, engineering, and business teams.
Role DNA
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4/5Autonomy Level
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Cover letter sample
Dear Hiring Team,
I am excited to apply for the Data Science Intern (Customer Success) role at Cresta. My experience with Python, SQL, data analysis, and introductory machine learning has prepared me to clean complex datasets, evaluate models, and communicate actionable insights clearly. I am particularly motivated by Cresta’s use of conversational AI to improve customer experiences and would welcome the opportunity to learn from cross-functional technical teams.
I would bring a curious, collaborative approach, strong analytical foundations, and careful documentation habits to support customer-facing data science work. Thank you for your consideration.
Sample interview questions
I would first clarify the business question and identify the relevant data sources and success metrics. I would inspect data types, missingness, duplicates, outliers, and potential leakage, then clean and transform the data with reproducible Python and SQL workflows. Finally, I would document assumptions and validate that the prepared dataset represents the intended population.
I would begin with a simple baseline model and a metric aligned to the business objective, such as precision, recall, F1, or ROC-AUC. I would use a train-validation-test split or cross-validation, compare performance against the baseline, inspect errors, and check for overfitting. I would also communicate model limitations and recommend monitoring after deployment.
I would use SQL to join the relevant tables, filter the appropriate date range and customer population, and aggregate metrics such as conversation volume, resolution rate, or sentiment by segment. I would validate results with spot checks and ensure that the query avoids duplicate records. I would then export or connect the result to a visualization for stakeholder review.
I would tailor the visualization to the audience and decision required, using clear labels, a concise headline, and only the metrics needed to explain the finding. I would pair the chart with a brief interpretation, note important caveats, and recommend a next step. For a dashboard, I would prioritize readability, consistent definitions, and filters that support common questions.
I would start by reproducing the issue and checking recent changes in input data, features, code, dependencies, and infrastructure. I would compare current performance with baseline metrics, review logs and data-quality checks, and isolate whether the issue is data drift, a pipeline problem, or model behavior. I would escalate findings clearly, document the resolution, and help establish monitoring to detect recurrence.
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day.
Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu, founded and led Google’s Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences.
Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta.
Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta’s co-founder and chairman is Sebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO, Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform, and co-founder, Tim Shi, an early member of Open AI.
Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it’s at Cresta.
About the role:
We are looking for a motivated Data Science Intern to join our team. This role offers hands-on experience working with real-world data, building models, and supporting data-driven decision-making. You will collaborate with data scientists, engineers, and business stakeholders to solve meaningful problems.
What You’ll Do :
- 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.
What We’re Looking For:
- 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, 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 recruiting@cresta.com.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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