Data Scientist

Champions Funding LLC; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Champions Funding LLC is seeking a data science professional to design, develop, and evaluate machine learning, statistical, and predictive models across departments. You will apply AI and ML techniques, including LLMs, to automate processes, improve decision-making, and generate business insights.

You will translate business objectives into analytic solutions, analyze large datasets, and collaborate with data engineering and business teams to deploy scalable pipelines and models in production

Qualifications

• Bachelor's degree in Mathematics, Data Science, Computer Science, Engineering, Physics, or another quantitative discipline; advanced degree preferred.
• Strong foundation in statistics, predictive modeling, machine learning algorithms, and programming languages such as Python and SQL.
• Experience with modern AI technologies, including deep learning, LLMs, generative AI, MLOps, or related frameworks.
• Experience deploying machine learning models in production environments.
• Understanding of cloud platforms and data science tools.
• Ability to balance accuracy, interpretability, speed, and risk in modeling decisions.
• Proven ability to communicate complex technical concepts to business leaders and cross-functional teams.
• Experience in financial services or regulated industries is a plus.
• Familiarity with model governance, risk management, or regulatory frameworks is a plus.

Responsibilities

• Design, develop, and evaluate ML, statistical, and predictive models across departments.
• Apply AI/ML techniques including LLMs and generative AI to automate processes and generate insights.
• Translate business objectives into analytic solutions that deliver measurable value.
• Analyze large datasets to identify trends and opportunities for improvement.
• Collaborate with data engineering and business teams to deploy scalable data pipelines and models.
• Evaluate model performance and system limitations with a focus on responsible deployment.
• Present findings and recommendations to executive leadership and stakeholders.
• Develop and monitor predictive models to ensure ongoing performance and reliability.
• Stay current with emerging AI technologies to identify opportunities for innovation.
• Support strategic BI projects, forecasting, automation, and operational optimization.
• Maintain documentation of models, methodologies, and development processes.

Skills

Machine learning

Python

SQL

Data analysis

LLMs / Generative AI

MLOps

Communication

Education

Bachelor's degree in Mathematics, Data Science, CS, Engineering or quantitative field

Tools

TensorFlow/PyTorch

AWS/GCP/Azure

Job description

• 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.