Data Scientist

CHAMPION FUNDING, LLC

United States

about 1 month ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

arc.dev

Tech stack

Artificial Intelligence Information Engineering Python (Programming Language) Machine Learning Tensorflow SQL Databases Cloud Platform System Large Language Models Deep Learning Model Validation Generative AI Information Technology

+4 more

Data Analytics Machine Learning Operations Data Pipelines Programming Languages

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.