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# Senior Data Scientist

- **Company:** KOMODO CONSULTING LLC
- **Location:** Lisbon, OH, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, Python (Programming Language), Object-Oriented Software Development, Software Deployment, Solution Deployment Descriptor, Data Processing, Data Lakes, Pyspark, Machine Learning Operations, Databricks
- **Published:** November 7, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pj26t28i0k

## About the Role

* Proven hands-on experience delivering end-to-end Data Science projects, from data exploration to solution deployment;
 * Strong Python skills, including object-oriented programming and the development of reusable, production-quality functions;
 * Experience with PySpark and big data processing environments;
 * Solid knowledge of Machine Learning and Deep Learning algorithms;
 * Strong foundation in exploratory data analysis and applied statistical methods;
 * Experience defining model monitoring strategies and building performance dashboards;
 * Ability to work autonomously and take full ownership of assigned projects, from requirements gathering to final delivery;
 * Strong communication skills, with experience engaging directly with business areas;
 * Experience with Databricks and MLflow is a plus;
 * Exposure to GenAI projects, even if partial, is valued.

## Description

* Own projects end-to-end, from initial data exploration and problem formulation through to modelling, evaluation, and handoff to the MLOps team for production deployment;
 * Engage directly with business stakeholders to understand requirements, translate them into data science problems, and present results clearly and effectively;
 * Develop and maintain clean, well-structured Python code, applying object-oriented programming principles and best practices;
 * Work with large-scale data stored in a Data Lake, leveraging PySpark and Databricks for data processing and model development;
 * Define and monitor model performance metrics, building dashboards to track model behaviour over time;
 * Manage the full lifecycle of assigned models, ensuring ongoing maintenance, iteration, and continuous improvement;
 * Contribute to GenAI initiatives alongside traditional Data Science projects, adapting fluidly between both contexts.