Data Scientist

Position Overview

Join Champions Funding LLC as a Data Scientist to develop, implement, and assess sophisticated machine learning and statistical models aimed at addressing diverse business challenges. Work across various departments to leverage cutting-edge AI technologies including large language models and generative AI to streamline operations, improve decision-making, and extract actionable insights.

Key Responsibilities

• Create and refine predictive, statistical, and machine learning models tailored to business needs across multiple teams.
• Utilize advanced AI techniques such as LLMs and generative AI to automate processes and generate strategic insights.
• Transform business goals into precise analytical solutions that deliver tangible value.
• Analyze extensive, complex datasets to uncover trends, patterns, and areas for enhancement.
• Collaborate with data engineers, IT, and business stakeholders to build scalable data pipelines and deploy models in production settings.
• Assess data integrity, model efficiency, and AI system constraints ensuring ethical and practical application.
• Communicate findings and technical concepts clearly to leadership and diverse audiences.
• Continuously monitor and fine-tune predictive models to sustain accuracy and reliability.
• Keep updated on AI and data science innovations to drive technological advancements within the company.
• Work cross-functionally to support strategic initiatives including business intelligence, automation, and forecasting.
• Maintain comprehensive documentation on models and methodologies for transparency and governance.
• Contribute to on-demand analytical projects providing data-driven recommendations to boost operational success.

Required Qualifications

• Bachelor’s degree in Mathematics, Data Science, Computer Science, Engineering, Physics, or related quantitative fields; advanced degrees preferred.
• Robust expertise in statistics, predictive analytics, machine learning algorithms, and programming languages like Python and SQL.
• Proven experience with contemporary AI technologies, including deep learning, LLMs, generative AI, and MLOps frameworks.
• Hands-on experience managing machine learning model lifecycle in production environments.
• Strong knowledge of cloud platforms and modern data science tools.
• Skill in evaluating model performance balancing accuracy, interpretability, speed, and risk with sound judgment in uncertain contexts.
• Effective communication skills to explain complex technical topics to both technical and non-technical stakeholders.
• Experience in financial services, mortgage lending, or regulated industries is advantageous.
• Familiarity with model governance, risk management, compliance, and regulatory standards is beneficial.