Manager, Data Science
About 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 shap e 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.
Requirements
- 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 Haves
- 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
Responsibilities
- 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 , 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.
- 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.
Benefits
- Medical, dental, vision insurance
- 401(k) matching
- Life insurance
- Pet insurance
- Competitive PTO (paid time off) policy
- Annual bonus opportunity
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What This Job Offers
Job Type
Full-time
Career Level
Manager
Number of Employees
501-1,000 employees
