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AI/ML Data Scientist #981755

Dexian • Full-time • Seffner, FL, US • 1w ago

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.