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# Data Analyst

- **Company:** WDS GLOBAL PARTNERS LLC
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $89,700.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Programming, Data Cleansing, Data Systems, Apache Hadoop, Python (Programming Language), Machine Learning, Power BI, Tensorflow, Systems Integration, Tableau (Software), Data Classification, Pytorch, Apache Spark, Keras, Scikit Learn, Information Technology, Splunk, Data Pipelines, Databricks
- **Published:** July 22, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/p6lb3fwlo3

## About the Role

* Degree in IT, Computer Science, Data Science or a related field.
 * At least four years of relevant professional experience.
 * Strong hands-on experience with Power BI.
 * Good programming skills in Python and/or R.
 * Experience with Tableau, Spark, Databricks, Splunk or Hadoop.
 * Experience with AI and machine learning technologies such as TensorFlow, Keras, PyTorch, Scikit-learn or RAG.
 * Experience deploying machine learning models into production.
 * Strong experience gathering business requirements.
 * Experience integrating, cleaning and testing data from new sources.
 * Experience improving AI prompts and classification accuracy.
 * Strong documentation and user-support skills.
 * Fluent English.

## Description

Data Analyst with strong Power BI, Python and Machine Learning skills to join a long-term international project.

You will work remotely within a development team, supporting a major client with dashboard enhancement, data pipelines, machine learning models and business-facing data solutions.

What You'll Do

 * Maintain and enhance Power BI dashboards.
 * Gather requirements directly from Business Units.
 * Build new data loads, dataset refreshes and reporting improvements.
 * Maintain and upgrade Power BI Data Gateway connections.
 * Develop and improve Python-based data classification pipelines.
 * Train, deploy and monitor machine learning models in production.
 * Improve model performance, classification accuracy and data quality.
 * Integrate new data sources and carry out data cleaning, testing and validation.
 * Create and refine AI prompts for classification use cases.
 * Document changes, processes and technical solutions.
 * Support users, manage incidents and provide training.
 * Contribute to security, risk, audit and incident-response activities.


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