Evolve data-driven solutions for the Customer Success organization by designing, developing, and producing advanced AI solutions.
Requirements
- Experience with Python (or R) and ML frameworks (scikit-learn, TensorFlow, PyTorch)
- Strong analytical mindset; able to translate model outputs into clear business recommendations
Responsibilities
- Collaborate with customer success, product, engineering, and sales teams to support the definition of KPIs and analytical approaches that address key business questions
- Assist in the design and development of machine learning models (e.g., classification, regression, NLP, or recommendation systems) under the guidance of senior data scientists
- Participate in the exploration of techniques for identifying at-risk customers, predicting churn, and evaluating the impact of product features and offerings
- Contribute to the development of recommendation engines and support research into collaborative filtering, content-based, and hybrid approaches
- Support data preprocessing, cleaning, and feature engineering tasks to prepare datasets for modeling and analysis
- Assist in monitoring model performance and analyzing key metrics such as accuracy, drift, and latency, as well as participate in A/B testing initiatives
- Work with the data science team in other orgs to translate business problems into data-driven solutions that align with organizational goals
Other
- Currently pursuing a Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field with strong academic track record(seniors preferred)
- Self-Starter: Thrives in ambiguous environments; able to iterate based on feedback
- Hands-on internship experience in product, data science, or related entrepreneurial roles
- Excellent at distilling complex technical concepts for non-technical audiences
