Sr. Data Science Manager

The Sr. Data Science Manager at LendingTree will be responsible for strategic planning and execution of Generative AI/ML solutions. This role involves overseeing multiple AI/ML projects, collaborating cross-functionally with teams, ensuring data quality, and presenting key insights to stakeholders.

Candidates for the Sr. Data Science Manager position at LendingTree should have 7-10 years of experience in data science, a Master's or PhD in a relevant field, expertise in machine learning and NLP, and proficiency in programming with Python, among others.

Ideal candidates for the Sr. Data Science Manager role at LendingTree should have considerable experience in developing and deploying AI/ML models in production, specifically using frameworks such as TensorFlow and PyTorch, and familiarity with cloud platforms like AWS.

The Sr. Data Science Manager plays a crucial role in fostering a collaborative and high-energy culture at LendingTree by mentoring junior members, sharing knowledge, and encouraging innovative ideas within the team.

The Sr. Data Science Manager position at LendingTree is located in Charlotte, North Carolina, with a requirement to work in-person at least three days a week, ideally from Tuesday to Thursday.

When answering this question, discuss specific projects where you implemented Generative AI techniques, focusing on the impact, challenges faced, and how data science principles guided your decisions.

Detail your processes for data validation, model testing, and monitoring in live environments. Emphasize the importance of data quality and iterative improvement.

Practice simplifying terminology and using relatable analogies. Focus on the business impact of the concept rather than technical details to enhance understanding.

Discuss frameworks you employ, such as Agile or SCRUM, and how you tailor communication and collaboration to meet team and project needs effectively.

Share specific examples of how you’ve deployed models into production environments, addressing tools and techniques that support continuous integration and delivery.

Illustrate your mentoring philosophy by mentioning specific instances where you provided guidance, feedback, or training, emphasizing the importance of fostering growth and confidence.

Highlight a specific project where you drove success through leadership and technical expertise while outlining key achievements and what you learned from the experience.

Discuss continuous learning efforts such as attending workshops, online courses, reading relevant publications, or participating in forums that enhance your knowledge and skills.

Share your preferences, explaining why you choose certain tools based on their features, ease of use, and how they help communicate insights effectively to stakeholders.

Emphasize the importance of cross-functional teamwork in successful projects, citing examples where collaboration helped achieve common goals or address challenges.