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# Data Scientist (Remote)

- **Company:** TRENT HOEK OUTDOORS LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $176,800.0 - $197,600.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, Code Review, Data Systems, Database Queries, Payment Systems, Graph Database, Python (Programming Language), Machine Learning, NoSQL, NumPy, Tokenization, Google Cloud, Snowflake, Pandas, Build Management, Scikit Learn, Information Technology, Machine Learning Operations, Databricks
- **Published:** October 20, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pj285hacpq

## About the Role

* Bachelor's or master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field. A PhD is preferred.
 * At least 7 years of experience in machine learning research or engineering.
 * At least 5 years of experience building large-scale, real-time machine learning systems in production, including hands-on development experience.
 * Expertise in machine learning, statistical modeling, and data analysis, with strong knowledge of the full ML lifecycle and experimentation.
 * Proficiency in Python, including Pandas, NumPy, and scikit-learn.
 * Strong SQL skills.
 * Demonstrated ability to lead technical solution design and execution while translating complex business needs into actionable technology solutions.
 * Excellent communication and collaboration skills, including the ability to influence technical and business stakeholders and communicate effectively with executives.

Preferred Qualifications

 * Experience with NoSQL or graph databases.
 * Experience in payments, fintech, or financial services.
 * Knowledge of payment systems, including the authorization lifecycle, tokenization, fraud and risk management, and real-time payments.
 * Experience with cloud platforms and data technologies such as AWS, GCP, Snowflake, Databricks, or Vertex AI.
 * Experience working in Agile development environments.
 * Background working in large organizations, mature machine learning teams, or regulated industries., * Candidates must be willing and able to work on a W-2 basis and transition to full-time employment following the contract period.

## Description

Our client is seeking a Principal Data Scientist to lead the development and expansion of Data Science and AI capabilities focused on end-to-end payment optimization. This remote, contract-to-hire position combines strategic technical leadership with hands-on machine learning expertise to build and deploy real-time models and intelligent decision engines., The Principal Data Scientist will work closely with machine learning engineers, product partners, and cross-functional teams to define technical strategy, guide architecture and solution design, and deliver production-ready ML systems. The role also involves mentoring experienced data scientists, establishing best practices, and shaping the operating model for machine learning research and development., * Define the technical vision and strategy for data-driven product initiatives focused on payment optimization and aligned with business goals.

 * Develop scalable, reusable capabilities for real-time machine learning models, including classification, ranking, optimization, rapid experimentation, and continuous monitoring.
 * Oversee and contribute to the conceptualization, development, deployment, operation, validation, and maintenance of machine learning models and update systems.
 * Lead architecture discussions, design reviews, code reviews, and selected implementation efforts to ensure production-grade ML solutions.
 * Establish and enforce best practices for machine learning modeling, evaluating and adopting modern tools, frameworks, and infrastructure.
 * Promote innovation, experimentation, and collaboration while mentoring senior data science professionals.
 * Partner with product, engineering, data, and compliance teams to integrate machine learning into products and communicate complex technical concepts to diverse audiences.
 * Collaborate with Data Science leaders to establish an ML research and development operating model that supports end-to-end delivery of business value.
 * Translate complex business requirements into practical technical solutions and guide solution design and execution.