Manager, Data Science

Manager, Data Science

* PLEASE NOTE:

this position is located in Charlotte, NC and requires attendance at our Southend office three days a week.

Candidates must be legally authorized to work in the United States. Lending Tree and its affiliates ("Lending Tree") will not provide or assume sponsorship for employment visas for this position, now or in the future.

Data Science and AI are reshaping how consumers find better financial outcomes, and Lending Tree is building what's next. We're looking for a Manager, Data Science to lead the team behind our models and define where they go from here. This is a role for a leader who loves both the craft and the people: you'll set the technical vision, grow a team of data scientists into tomorrow's leaders, and make sure every model we ship drives measurable business results.

You'll chart the team's road map, from spotting where machine learning and AI can create the most value to taking solutions from prototype to production  you're equally comfortable debating model architecture, weighing business tradeoffs, and developing great talent, this is your chance to shape the future of data science at Lending Tree.

• Lead, mentor, and develop a team of data scientists, fostering technical excellence, growth, and scientific rigor.
• Partner with senior stakeholders to identify and prioritize the opportunities where machine learning and AI can deliver the most value.
• Oversee the design, development, and deployment of scalable, reproducible models, and guide the team through data acquisition, feature engineering, and the full model lifecycle from prototype to production.
• Promote best practices in experimentation, modeling, validation, and monitoring, and raise standards for documentation, testing, versioning, and code review.
• Champion explainability, fairness, and reliability in every model-driven solution.
• Translate complex analytical findings into clear, actionable insights for technical and business audiences, and drive alignment across business units so models meet real-world needs.

You'll lead a team of data scientists and work hand in hand with engineering, MLOps, product, analytics, and platform leaders, as well as senior business stakeholders. This is a highly collaborative role: you'll be a trusted partner in building data-driven decision-making into our products and operations, and a hands-on guide for your team where it counts.

• A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related field (PhD a plus).
• 7+ years of experience in applied data science, including experience in a leadership or people management role.
• A track record of leading teams through the full ML lifecycle: data preparation, modeling, validation, deployment, and monitoring.
• Advanced proficiency in Python, SQL, and data science libraries (Num Py, Pandas, Scikit-learn, PyTorch, Tensor Flow).
• Experience with cloud-based ML platforms (AWS Sage Maker or Snowpark preferred).
• A solid understanding of MLOps, reproducibility, and governance practices.
• Strong analytical, organizational, and problem-solving skills, with a history of business impact.
• Excellent written and verbal communication skills, with the ability to influence technical and executive audiences.

• Experience in fintech or other data-rich, high-scale consumer businesses.
• A background in software engineering, model deployment, or data platform integration.
• Experience managing hybrid teams (on-site and remote).
• In-depth knowledge of GenAI and LLM capabilities, ideally including building Retrieval Augmented Generation (RAG) and agentic workflows.
• Curiosity, a collaborative spirit, and a passion for continuous learning.
• Comfort in fast-paced, highly ambiguous, cross-functional environments, and a drive to build scalable, responsible, and impactful data science and AI solutions that move the business forward.

• Models move from prototype to production reliably, with consistent standards for testing, documentation, versioning, and monitoring.
• Data science and AI work is prioritized with business partners and tied to measurable outcomes.
• Stakeholders across Analytics, Product, and Platform see the team as a trusted partner and use its insights to make decisions.
• Your team is growing technically and professionally, with clear development paths and strong engagement.

We're a collaborative, entrepreneurial…