Jobs via Dice
Data Scientist AI/ML
Location: Tampa, FL
Domain: Data Management
Long Term Contract. Looking for W2 Candidates. No C2C.
Responsibilities
Translate complex business challenges into clear, actionable AI/ML strategies and comprehensive technical roadmaps, ensuring alignment with organizational goals.
Guide, mentor, and develop a high-performing team of data scientists and machine learning engineers, fostering a collaborative culture of innovation, continuous learning, and technical excellence.
Oversee the entire machine learning lifecycle, from problem definition and data exploration to model design, training, validation, deployment, monitoring, and ongoing optimization.
Lead the successful deployment of robust, scalable, and high-impact ML solutions into production environments, ensuring they generate measurable and significant business value.
Champion MLOps best practices, ensuring robust model governance, versioning, testing, and monitoring for all AI solutions.
Actively research, evaluate, and integrate new AI technologies, frameworks (including Agentic frameworks), tools, and cutting-edge research findings to maintain a competitive edge and drive innovation.
Collaborate effectively with cross-functional teams, including engineering, product, and business units, to understand requirements, manage expectations, and ensure successful project delivery.
Apply a strong understanding of ethical AI principles, fairness, transparency, and data privacy throughout the design, development, and deployment of all AI solutions.
Qualifications
Overall 12+ years of experience and min 8+ years of progressive experience in data science roles, with a significant focus on leading AI/ML initiatives.
Demonstrated proficiency in Agentic frameworks (e.g., Langgraph, CrewAI), Python, and SQL.
Deep expertise in the end-to-end ML lifecycle, including model design, training, validation, deployment, and monitoring.
Proven experience deploying scalable ML solutions in production environments.
Proficiency in major cloud platforms (e.g., AWS, Azure, Google Cloud Platform) for scalable AI solution development and deployment, including relevant services (e.g., SageMaker, Azure ML, Vertex AI).
Experience with Machine Learning Frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Familiarity with data processing and manipulation libraries/tools like Pandas and Apache Spark.
Understanding of MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes) for model lifecycle management.
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Domain: Data Management
Long Term Contract. Looking for W2 Candidates. No C2C.
Responsibilities
Translate complex business challenges into clear, actionable AI/ML strategies and comprehensive technical roadmaps, ensuring alignment with organizational goals.
Guide, mentor, and develop a high-performing team of data scientists and machine learning engineers, fostering a collaborative culture of innovation, continuous learning, and technical excellence.
Oversee the entire machine learning lifecycle, from problem definition and data exploration to model design, training, validation, deployment, monitoring, and ongoing optimization.
Lead the successful deployment of robust, scalable, and high-impact ML solutions into production environments, ensuring they generate measurable and significant business value.
Champion MLOps best practices, ensuring robust model governance, versioning, testing, and monitoring for all AI solutions.
Actively research, evaluate, and integrate new AI technologies, frameworks (including Agentic frameworks), tools, and cutting-edge research findings to maintain a competitive edge and drive innovation.
Collaborate effectively with cross-functional teams, including engineering, product, and business units, to understand requirements, manage expectations, and ensure successful project delivery.
Apply a strong understanding of ethical AI principles, fairness, transparency, and data privacy throughout the design, development, and deployment of all AI solutions.
Qualifications
Overall 12+ years of experience and min 8+ years of progressive experience in data science roles, with a significant focus on leading AI/ML initiatives.
Demonstrated proficiency in Agentic frameworks (e.g., Langgraph, CrewAI), Python, and SQL.
Deep expertise in the end-to-end ML lifecycle, including model design, training, validation, deployment, and monitoring.
Proven experience deploying scalable ML solutions in production environments.
Proficiency in major cloud platforms (e.g., AWS, Azure, Google Cloud Platform) for scalable AI solution development and deployment, including relevant services (e.g., SageMaker, Azure ML, Vertex AI).
Experience with Machine Learning Frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Familiarity with data processing and manipulation libraries/tools like Pandas and Apache Spark.
Understanding of MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes) for model lifecycle management.
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