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# Data Scientist 100% Remote - Must be US Citizen due to Public Trust Clearance

- **Company:** Cypress
- **Location:** United States (Remote available)
- **Salary:** $150,000.0 - $170,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Big Data, Cloud Computing, Computer Programming, Data Visualization, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, NumPy, Power BI, Tensorflow, SQL Databases, Data Streaming, Tableau (Software), Feature Engineering, Model Validation, Pandas, Matplotlib, Scikit Learn, Information Technology, Machine Learning Operations, Multiaccess Edge Computing, Stream Analytics, Data Pipelines, Databricks
- **Published:** September 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=8f4859d814e3f8fa

## About the Role

* Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field (or equivalent hands-on experience).
 * 3+ years of professional experience in data science or applied machine learning.
 * Strong programming skills in Python (e.g., Pandas, NumPy, Scikit-learn) with solid SQL experience.
 * Experience building and deploying machine learning models in production environments.
 * Hands-on experience with Databricks or similar platforms for large-scale data processing and model development. Databricks Certification is highly desired
 * Familiarity with cloud platforms (AWS preferred) and ML pipelines.
 * Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, or Seaborn).
 * Strong understanding of statistical methods, predictive modeling, and model evaluation techniques.
 * Excellent problem-solving, analytical, and communication skills.
 * Experience with streaming or near real-time analytics is a plus.
 * Certifications in machine learning or cloud platforms are a plus., * Data science: 3 years (Required)
 * Databricks: 1 year (Required)

License/Certification:

 * databricks certification (Preferred)

## Description

* Develop, train, and deploy machine learning and statistical models to solve business problems and extract actionable insights.
 * Analyze large, complex datasets (structured and unstructured) to identify trends, patterns, and opportunities.
 * Collaborate with data engineers and analysts to design data pipelines, define feature engineering strategies, and ensure data readiness for modeling.
 * Build and optimize predictive models using modern ML frameworks and tools.
 * Conduct exploratory data analysis (EDA), hypothesis testing, and model evaluation.
 * Communicate findings and insights to stakeholders through visualizations, reports, and presentations.
 * Monitor model performance, retrain models as needed, and ensure scalability and reliability in production.
 * Stay up to date with emerging trends in machine learning, AI, and advanced analytics.