Job Description

Job Title: AI Data Scientist

Location: Seffner, FL

Employment Type: Contract-to-Hire

Position Overview

We are seeking an experienced AI Data Scientist to design, develop, and implement advanced machine learning and artificial intelligence solutions leveraging Databricks , Python , Azure , and SQL . The ideal candidate will have strong experience building and deploying data-driven models in cloud environments, collaborating with data engineers and business stakeholders to turn complex datasets into actionable insights.

Key Responsibilities

• Develop, train, and deploy machine learning and AI models for predictive analytics, automation, and optimization use cases.
• Utilize Databricks for scalable data processing, model training, and orchestration of ML pipelines.
• Write efficient and reusable Python code for data preprocessing, feature engineering, and model development.
• Work within Azure Machine Learning and Azure Data Factory environments to manage model lifecycles and data workflows.
• Query, clean, and analyze large datasets using SQL to extract meaningful trends and patterns.
• Collaborate with data engineers , analysts , and business stakeholders to understand objectives and deliver data-driven solutions.
• Evaluate model performance using appropriate metrics and continuously refine algorithms for accuracy and efficiency.
• Implement MLOps best practices for continuous integration and deployment of ML models.
• Develop dashboards and visualizations to communicate insights and performance results.

Required Skills & Qualifications

• 3–7 years of experience as a Data Scientist or Machine Learning Engineer.
• Strong hands-on experience with Databricks (including notebooks, Delta Lake, and MLflow).
• Advanced proficiency in Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, etc.).
• Solid experience with Azure Cloud Services (Azure ML, Data Factory, Synapse, Blob Storage).
• Strong SQL skills for data extraction, transformation, and analysis.
• Experience building and deploying ML models in production environments.
• Understanding of data pipelines, feature engineering, and model evaluation techniques .
• Familiarity with MLOps concepts and version control (Git/GitHub).
• Excellent problem-solving and communication skills; ability to explain complex concepts to non-technical stakeholders.

Preferred Qualifications

• Master’s or PhD in Computer Science, Data Science, Statistics, Applied Mathematics , or related field.
• Experience with Power BI or Tableau for data visualization.
• Knowledge of Big Data tools (Spark, Hive) or other cloud platforms (AWS, GCP).
• Experience in natural language processing (NLP) or generative AI is a plus.

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