Data Scientist
• Design, develop, and evaluate machine learning, statistical, and predictive models to solve complex business challenges across multiple departments. • Apply modern artificial intelligence and machine learning techniques, including large language models (LLMs), generative AI, and advanced analytics, to automate processes, enhance decision-making, and generate business insights. • Translate business objectives into well-defined analytical, statistical, and machine learning solutions that deliver measurable business value. • Analyze large, complex datasets to identify trends, patterns, opportunities, and operational improvements. • Partner with data engineering, IT, and business teams to develop scalable data pipelines and deploy machine learning models into production environments. • Evaluate data quality, model performance, and AI system limitations while ensuring responsible, ethical, and practical implementation of predictive models. • Present analytical findings, recommendations, and technical concepts clearly to executive leadership and both technical and non-technical stakeholders. • Develop, monitor, and optimize predictive models, ensuring ongoing performance, accuracy, and reliability through continuous improvement. • Stay current with emerging technologies, AI advancements, machine learning methodologies, and data science best practices to identify opportunities for innovation. • Collaborate across departments to support strategic initiatives, business intelligence projects, forecasting, automation, and operational optimization. • Maintain thorough documentation of models, methodologies, assumptions, and development processes to support transparency, reproducibility, and governance. • Support ad hoc analytical projects and provide data-driven recommendations that improve business performance and operational efficiency.
Requirements• Bachelor's degree required in Mathematics, Data Science, Computer Science, Engineering, Physics, or another quantitative discipline; advanced degree preferred. • Strong technical foundation in statistics, predictive modeling, machine learning algorithms, and programming languages such as Python and SQL. • Demonstrated experience working with modern AI technologies, including deep learning, large language models (LLMs), generative AI, MLOps, or related machine learning frameworks. • Experience developing, deploying, and maintaining machine learning models in production environments. • Strong understanding of cloud computing platforms and modern data science tools and technologies. • Ability to evaluate model performance, balance trade-offs between accuracy, interpretability, speed, and risk, and apply sound judgment in ambiguous situations. • Experience communicating complex technical concepts to business leaders and collaborating effectively with cross-functional teams. • Experience within financial services, mortgage lending, or other highly regulated industries preferred. • Familiarity with model governance, model risk management, compliance, or regulatory frameworks is a plus.
Bachelor's in quantitative field required (advanced degree preferred); experience with statistics, predictive modeling, ML, LLMs, MLOps, Python and SQL; production ML deployment and cloud familiarity.
Key Responsibilities
- developing models
- analyzing data
- presenting findings
Skills & Tools
Python, SQL, deep learning, LLMs, generative AI, MLOps
Job Details
- Category: Data and Analytics
- Seniority: Mid Level
- Commitment: Full Time
- Workplace: Remote — United States
- Languages: English
About Champions Funding LLC
A financial services company focused on mortgage lending and related analytics. — Industry: Finance