Role overview
The Lifecycle Marketing team is responsible for driving user & revenue growth for Robinhood. As we expand our suite of product offerings, we want to make sure we are taking a personalized approach to driving growth & engagement, by helping each user discover & engage with the right products & features within Robinhood that they might find most valuable. As we embark on this path, we are looking for a senior MLE to come in and lead our personalization efforts, and conceive, build & execute on a roadmap for how to effectively personalize our experiences to drive user growth & engagement.
What you'll work on
As a Machine Learning Engineer in our team, your primary focus will be on the implementation and evaluation of machine learning algorithms through rigorous experimentation and testing methodologies. Your responsibilities will include:
- Model Development and Implementation: Develop and implement scalable machine learning models focusing on advanced ranking and recommendation systems, including expertise in Collaborative Filtering, Content-Based Filtering, and Hybrid models, alongside proficiency in Learning to Rank (LTR) techniques for effective prioritization. Additionally, design reinforcement learning algorithms and apply multi-armed bandit strategies to optimize decision-making in dynamic environments, balancing exploration and exploitation.
- A/B Testing and Experimentation: Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance, and analyzing results.
- Data Analysis and Insight Generation: Analyze experimental data to extract actionable insights. Use statistical techniques to validate the findings and ensure their relevance and accuracy.
- Cross-Functional Collaboration: Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements.
- Documentation and Reporting: Maintain comprehensive documentation of models, experiments, and findings. Prepare reports and presentations to communicate results to different stakeholders.