What You’ll Do: Twitter’s mission is to be a global platform for public conversation. The Singapore Data Science team works closely with Consumer Product groups across Clients, Performance, and Growth to design metrics, perform advanced analyses, and run experiments to improve our product for Global markets. You’ll work closely with our partners in Product, Engineering, Design to advance a deep understanding of how users are using our product, inform product decisions and influence the company strategy.
Who You Are:
You have a broad and deep technical background in data science and analytics, and are proficient at analyzing large structured and unstructured datasets to derive insights. You are highly technical and hands on but also demonstrate a strong product mindset. You provide strong technical mentorship to other data scientists and uplevel the overall technical bar of the DS team.
You take responsibility for the group’s short-term and long-term strategy, define the team's roadmap, success metrics, and priorities in close collaboration with multi-functional partners. You drive a culture of trust, respect, and inclusion within your teams.
You are great at:
- Delivering actionable results through your combination of data science solutions, product thinking, statistical knowledge, and deep understanding of data.
- Collaborating with product managers, engineers, designers, and user research to drive product impact
- Distilling complex analytical results into presentable, digestible, and actionable feedback for product and engineering teams
- Leading and prioritizing projects
- Creating a culture of rigor and scientific inquiry
- Understanding consumer products
- 4+ years experience in data science and quantitative analysis (preferably in an engineering or product role)
- Strong programming skills (Python, R, SQL) and experience using common analysis tools (Hive, Presto, Scalding)
- Strong bias to action, creative problem solving mindset, and proactive communication
- An advanced degree in a quantitative domain such as Computer Science, Machine Learning, Statistics, Operations Research, or similar. Masters and PhD is a plus but not required
- Proficiency with ML and data analytics technologies such as Spark, Airflow, TensorFlow, etc.