Manager, Data Science

NOTE: This role requires the candidate to be in or near Charlotte, NC. In‑office presence is required three days a week. Additionally, this position does not offer visa sponsorship.

The Manager, Data Science will lead a team of data scientists to design, develop, and deploy models that drive measurable business outcomes across Lending Tree. This role combines technical leadership with strategic oversight — ensuring scientific rigor, operational excellence, and cross‑functional impact.

You will play a key role in shaping the team direction, mentoring talent, and collaborating with engineering, product, analytics, and business stakeholders to deliver scalable, high‑quality data science/AI solutions. The ideal candidate is equally comfortable discussing model architectures, business tradeoffs, and team development strategies.

• Lead, mentor, and develop a team of data scientists, fostering technical excellence and growth.
• Collaborate with senior stakeholders to identify and prioritize opportunities where machine learning and AI can deliver value.
• Promote best practices in experimentation, modeling, validation, and monitoring to ensure robust, production‑grade solutions.
• Oversee the design, development, and deployment of data science models, ensuring scalability, reproducibility, and operational performance.
• Guide the team through data acquisition, feature engineering, and model lifecycle management from prototype to production.
• Partner with MLOps and engineering to streamline workflows and monitor models in production environments.
• Review and enhance model documentation, testing, and versioning standards.

• Apply expertise in Python, SQL, and ML frameworks (Scikit‑learn, PyTorch, Tensor Flow, etc.) to provide hands‑on guidance where needed.
• Lead code reviews and establish quality control standards for data science deliverables.
• Champion explainability, fairness, and reliability in all model‑driven solutions.

• Translate complex analytical findings into actionable business insights for diverse audiences.
• Collaborate closely with Analytics, Product, and Platform leaders to integrate data‑driven decision‑making into products and operations.
• Drive alignment across business units to ensure models address real‑world needs and deliver measurable impact.

• 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, with experience in a leadership or people management role.
• Proven ability to lead teams through 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).
• Solid understanding of ML Ops, reproducibility, and governance practices.
• Strong analytical, organizational, and problem‑solving skills with a track record of business impact.
• Excellent written and verbal communication skills; capable of influencing technical and executive audiences.

• Experience in fin‑tech or other data‑rich, high‑scale consumer businesses.
• Background in software engineering, model deployment, or data platform integration.
• Experience managing hybrid teams (on‑site and remote).
• In-depth knowledge and experience in leveraging GenAI & LLM capabilities, building Retrieval Augmented Generation/agentic workflows preferred.

Lending Tree is the nation’s leading online lending marketplace. We connect consumers with multiple lenders so they can easily compare options and find the right fit — from mortgages and personal loans to credit, savings, and insurance products.

Our founder, Doug Lebda, started Lending Tree in 1996 after his own frustrating house‑hunting experience. What began as a simple idea to make loan shopping easier has grown into a platform that empowers millions of people to make smarter financial decisions every day.

What else you should know:

• We’re a publicly traded company (NASDAQ: TREE).
• We’v…