The Data Science team is chartered to relentlessly improve all 2U revenue operations by surfacing insights, and identifying and enabling product and marketing innovations leveraging analytics, experimentation and modeling.
As a Data Scientist, you’ll partner with a diverse range of cross-functional business partners to uncover new opportunities, design, execute, and analyze experiments, and deliver solutions that have a significant business impact and implications for our learners. You will help drive innovations through effective identification and application of analytics, causal inference, experimentation, and machine learning. This is a high-impact role in which you will have a direct influence on how product and marketing decisions are made. You will play a key role in spurring innovations to drive growth, engagement, and retention at a critical moment in 2U’s history.
- Effectively identify and apply analytics, causal inference, experimentation, and machine learning techniques for given business problems
- Proactively perform data exploration on engagement behaviors to discover future opportunities
- Apply modeling and machine learning techniques to business problems, including engagement and retention forecasts and valuation models
- Collaborate with cross-functional stakeholders from product, marketing, engineering, admissions, operations, etc., to develop and deploy insights and models at scale
- Relentlessly improve data science team operations by providing feedback and mentorship to team members
- Present your insights to all levels of the company
- 3+ years of relevant working experience in a quantitative role performing statistical modeling and analysis. (We are open to hiring mid-level to senior candidates for this role.)
- Strong statistical knowledge and intuition – ideally utilized in experimentation, predictive modeling, forecasting or other analytics settings
- Experience in building real-world machine learning models with demonstrated business impact
- Strong SQL and quantitative programming skills in Python or R
- Comfort working independently to take ambiguous problems and solve them down in a structured, hypothesis-driven, data-supported way
- Excitement about influencing product strategies in a fast-paced, cross-functional environment
- Ability to communicate technical and statistical concepts clearly and concisely among audiences at many different levels