Data Scientist

This is a fully remote position, open to applicants in Florida, +1 more state.

📋 Description

• Extract, analyze, and interpret intricate structured and unstructured datasets to produce actionable insights for both internal stakeholders and external clients.

• Lead the design, development, validation, and deployment of predictive, statistical, and machine learning models that address significant business challenges.

• Create and implement data models and algorithms that support forecasting, optimization, anomaly detection, personalization, and decision automation.

• Collaborate with product, engineering, and business teams to pinpoint high-value opportunities where data science can yield measurable results.

• Transform analytical insights into production-grade data products, APIs, and scalable solutions.

• Design and conduct experiments (A/B testing, hypothesis testing) and provide clear, data-driven recommendations.

• Develop dashboards, visualizations, and self-service analytics tools to make insights accessible to both technical and non-technical users.

• Analyze data to enhance product performance, operational efficiency, customer experience, and revenue outcomes.

• Assess new data sources and data collection methods to ensure quality, accuracy, and relevance.

• Establish frameworks and processes to monitor model performance, drift, and data integrity over time.

• Document methodologies, assumptions, and results to guarantee transparency, reproducibility, and knowledge sharing.

• Effectively communicate insights and recommendations to senior leadership and cross-functional stakeholders.

⛳️ Requirements

• Bachelor’s degree in engineering, Mathematics, Statistics, Machine Learning, Analytics, Information Systems, or a related quantitative field; a Master’s degree is highly preferred.

• 5–7+ years of experience in data science, advanced analytics, or similar roles delivering production-grade data solutions.

• Advanced proficiency in Python for data analysis and machine learning (including libraries such as pandas, NumPy, scikit-learn, XGBoost, etc.).

• Expert-level SQL skills for complex data querying, transformation, and performance optimization.

• Strong experience with machine learning techniques, encompassing supervised/unsupervised learning, feature engineering, and model evaluation.

• Solid foundation in statistics, including experiment design, hypothesis testing, and inferential analysis.

• Experience with big data technologies and distributed systems (such as Spark, Hadoop, Hive, Presto, etc.).

• Hands-on experience with containerization and environment management (using Docker, Conda) and modern data pipelines.

• Proven track record of deploying and maintaining models in production environments.

• Experience with cloud platforms (AWS, Azure, or GCP) for data and ML workloads.

• Familiarity with data visualization / BI tools (Tableau, Power BI, or similar).

• Strong communication skills with the capability to translate complex analyses into clear business insights.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible work hours

• Paid time off

• Remote work options