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# Data Scientist

- **Company:** ASSOCIATION OF DATA SCIENTISTS AND DATA ENGINEERS
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $30,000.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Computer Programming, Continuous Integration, Data Architecture, Data Integration, Distributed Systems, Python (Programming Language), Machine Learning, Software Engineering, Feature Engineering, Pandas, Containerization, Pyspark, Scikit Learn, Information Technology, Deployment Automation, Api Design, Software Version Control, Data Pipelines, Docker
- **Published:** July 23, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/lk7dxcexhp

## About the Role

* Bachelor's or Master's in Data Science, Computer Science, Software Engineering, or a related field.
 * 3+ years of experience in data science, machine learning deployment, or a similar hands-on technical role.
 * Solid understanding of data science and machine learning concepts, with practical experience adapting models to real-world data and constraints.
 * Strong programming skills in Python, including the data science ecosystem (e.g. pandas, scikit-learn), with solid software engineering fundamentals (version control, testing, CI/CD).
 * Experience with PySpark for large-scale data processing and feature engineering.
 * Experience deploying and integrating data science solutions in client or production environments, including working with APIs, cloud platforms, and containerization (e.g., Docker).
 * Familiarity with distributed systems and the challenges of building and operating data-intensive solutions at scale.
 * Excellent communication skills and a client-focused mindset, with the ability to explain models and technical concepts to non-technical stakeholders.
 * Strong problem-solving skills and the ability to work independently in ambiguous, fast-moving situations.
 * Willingness to travel to client sites when needed.

## Description

* Work closely with clients to understand their data landscape, technical environment, and business objectives, translating these into effective data science deployment strategies.
 * Deploy, configure, and integrate JTA's data science and ML solutions into client systems, ensuring models run reliably and deliver value in production.
 * Adapt and extend existing models and data pipelines to fit client-specific data, constraints, and requirements, writing robust, maintainable code across the stack.
 * Act as a technical bridge between clients and JTA's internal data science and engineering teams, relaying feedback and shaping solutions accordingly.
 * Troubleshoot issues across data pipelines and production models, monitoring performance and providing hands-on support to ensure solutions perform as intended.
 * Collaborate with business stakeholders and the sales team to translate data science outcomes into clear business value.


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