Location: Sunrise, FL
Experience Required: 6-10 Years
We are seeking a highly skilled Data Scientist with strong expertise in Python, PostgreSQL, and PyTest to design, develop, and deliver advanced data-driven solutions. This role focuses on building statistical and predictive models, performing deep analytical research, and ensuring high-quality, test-driven data pipelines for enterprise-grade applications.
The ideal candidate is analytical, detail-oriented, and capable of translating complex datasets into actionable business insights while maintaining robust testing and data integrity standards.
Design, build, and optimize advanced statistical and predictive data models .
Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
Apply statistical techniques and machine learning methods to solve complex business problems.
Develop and optimize data workflows using Python .
Write efficient, scalable queries using PostgreSQL for large datasets.
Ensure data quality, consistency, and integrity across data sources.
Implement automated testing frameworks using PyTest for data pipelines and models.
Validate model outputs, transformations, and data accuracy.
Ensure adherence to test-driven development (TDD) and best practices.
Work closely with cross-functional teams including Data Engineers, Product Managers, and Business Analysts.
Translate analytical findings into clear insights, dashboards, and reports for stakeholders.
Document methodologies, assumptions, and model performance metrics.
Monitor model performance and recalibrate as required.
Identify opportunities to improve efficiency, scalability, and reliability of data solutions.
Stay updated with the latest trends in data science, analytics, and testing frameworks.
Strong hands-on experience with Python for data analysis and modeling.
Proficiency in PostgreSQL , including complex queries and performance tuning.
Solid experience with PyTest for automated testing of data pipelines and models.
Experience with statistical analysis, hypothesis testing, and feature engineering.
Familiarity with data visualization tools (Matplotlib, Seaborn, Plotly, etc.).
Experience building predictive models using machine learning techniques.
Knowledge of supervised and unsupervised learning algorithms.
Strong understanding of data preprocessing, normalization, and validation techniques.
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
Experience working with enterprise-scale or regulated environments.
Exposure to CI/CD pipelines for data science workflows.
Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus.
Strong analytical and problem-solving mindset.
Excellent communication skills with the ability to explain complex concepts simply.
High attention to detail and commitment to data accuracy.
Ability to work independently and collaboratively in fast-paced environments.
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