Lead Data Scientist

As a Lead Data Scientist at Babylist, you’ll redefine how millions of users search and discover the products they will love as they prepare for one of life’s biggest events. You will partner with other Data Scientists, Product Managers and Engineers to understand users needs and improve the experience of building registries and shopping at Babylist.

• You will be responsible for building and owning the next generation of personalization and product/content recommendation systems that will make the experience for our millions of Babylist users unique to them.
• Facilitate collaboration with other engineers, product managers, and designers to build best-in-class ML powered search, ranking, and recommender systems.
• You have prowess and past experience in a multitude of recommendation technologies, empowering you to understand the challenges of making discovery better continuously by hypothesis, modeling, and experimentation.
• Be a data leader within Babylist.
• Mentor and collaborate closely with other engineers and become a valued member of a diverse and autonomous team.
• Continuously improve our product by innovating on the service through the usage of A/B tests.

• BS, MS or Ph.D. in computer science, engineering, mathematics, machine learning, (computational) physics or statistics.
• You must be fluent in Python & SQL.
• Strong mathematical, statistical methods and analytical skills.
• Experience working with ML frameworks like TensorFlow, PyTorch, Scikit-learn, Spark ML, Torch, or RankFM.
• You have at least 5+ years of professional experience working in a product-driven environment, out of which 3+ years are in one or more of the following: recommendation systems, search, natural language processing, or similar.
• Experience with training systems based on large scale implicit user behavior including handling feedback loops.
• You care about agile software processes, data-driven development, reliability, and responsible experimentation.
• Experience mentoring and growing collaborative teams.