Manager, Data Science

*PLEASE 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 POSITION

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

You will play a key role in helping shape 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. 

KEY RESPONSIBILITIES

Leadership & Strategy:

• 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. 

Model Development & Delivery:

• 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. 

Technical Expertise:

• Apply expertise in Python, SQL, and ML frameworks (Scikit-learn, PyTorch, TensorFlow, 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. 

Stakeholder Engagement & Communication:

• 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. 

QUALIFICATIONS

• 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 (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow). 

• Experience with cloud-based ML platforms (AWS SageMaker 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. 

NICE TO HAVE

• 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 

COMPANY

LendingTree is the nation’s largest online lending marketplace. That means we connect customers with multiple lenders so they find the best deals on loans, credit cards, savings accounts and insurance. Our goal is to help people save money, and we believe the best way to do that is by giving them a way to shop for loans and compare lenders so they make their best financial choices.

Our story began in 1996, when our founder, Doug Lebda, set out to make the home-buying process easier after his own frustrating house-hunting experience. What started as a simple idea to help people find better mortgage options has grown into a platform that empowers millions of consumers to compare and choose the financial products that fit their lives best — including loans, credit, savings, and insurance products.

What else you should know: 

• We’re a publicly-traded company (TREE).
• We’ve welcomed several other companies into the LendingTree family to augment our efforts at helping borrowers make their most sensible financial choices.
• We’ve built a LendingTree app and LendingTree dashboard to give consumers tools to manage and monitor their financial health.

CULTURE

We’re looking for leaders who foster curiosity, collaboration, and continuous learning. The ideal candidate thrives in fast-paced, highly ambiguous, cross-functional environments, and is passionate about building scalable, responsible, and impactful data science/AI solutions that move the business forward. 

We’re a fast-paced company with an entrepreneurial bend. We work hard and test our products often. We’re collaborative, ambitious, candid and high-energy. Our teammates are some of the brightest, most talented people you’ll ever work with. We care more about your smarts than we do about the kinds of clothes you wear (but please, do wear clothes to work!), and we’re pretty good about rewarding innovation, creativity and the knack for just getting stuff done (we even have an award for employees called the GSD, “Get Stuff Done”). 

Come work with us!

LendingTree is the kind of company that not only promotes diversity and inclusion; we thrive because of these values. We do not discriminate based on race, color, religion (or creed), gender, gender expression, age, national origin, disability, marital status, sexual orientation or military status.

CCPA Disclosure