Salesforce is looking to evolve its data-driven solutions and address key business questions through advanced AI solutions, specifically in the area of customer success
Requirements
- Experience with Python (or R) and ML frameworks (scikit-learn, TensorFlow, PyTorch)
- 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)
- Hands-on internship experience in product, data science, or related entrepreneurial roles (preferred)
- Strong analytical mindset; able to translate model outputs into clear business recommendations
- Technical proficiency in machine learning and AI development
- Experience with data preprocessing, cleaning, and feature engineering
- Familiarity with A/B testing and model performance metrics
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 a related field (seniors preferred)
- Strong communication and influence skills; able to distill complex technical concepts for non-technical audiences (preferred)
- Ability to thrive in ambiguous environments; able to iterate based on feedback
- Excellent analytical mindset and business acumen
- Ability to present findings, visualizations, and insights to team members and stakeholders in a clear and concise manner
