Data Science Architect

Title : Data Science Architect

Location : Nashville TN

Duration : Long Term

We are seeking a highly skilled and experienced Data Science Architect to lead the design, development, and implementation of advanced data solutions. The ideal candidate will possess strong expertise in data science, machine learning, big data platforms, and architectural frameworks to deliver innovative solutions that drive business insights and decision-making.

Key Responsibilities:
• Design and implement scalable and efficient data science architectures to support advanced analytics, AI, and machine learning solutions.
• Define best practices for data science workflows, including data preprocessing, feature engineering, model development, and deployment.
• Develop reusable frameworks and templates for data pipelines and machine learning models.
• Collaborate with stakeholders to define data science strategies aligned with business goals.
• Identify opportunities for leveraging data to drive business insights and operational efficiencies.
• Recommend tools, platforms, and frameworks that align with the organization's data ecosystem.
• Lead the design and implementation of data pipelines for real-time and batch processing using big data technologies (e.g., Hadoop, Spark, Kafka).
• Ensure the scalability, reliability, and performance of deployed data science models and systems.
• Stay updated with emerging technologies, tools, and trends in data science and incorporate them into the architecture when appropriate.
• Work closely with data engineers, data scientists, and business analysts to ensure cohesive implementation of data science projects.
• Mentor and guide data science teams on best practices, frameworks, and tools.
• Collaborate with IT and DevOps teams to deploy machine learning models into production environments.
• Establish governance frameworks for data access, privacy, and security to ensure compliance with industry standards and regulations.
• Define data validation and quality assurance standards for model outputs and datasets.
• Develop monitoring frameworks for deployed machine learning models to ensure continuous performance and accuracy.
• Implement feedback loops for model retraining and optimization.

Qualifications and Requirements:

Education:

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field. A Ph.D. is a plus.

Experience:
• 8+ years of experience in data science, machine learning, or data engineering roles.
• 3+ years of experience in designing and implementing large-scale data science architectures.

Technical Skills:
• Proficiency in programming languages like Python, R, Java, or Scala.
• Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Expertise in big data platforms (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP).
• Hands-on experience with data visualization tools (e.g., Tableau, Power BI, matplotlib).
• Experience with version control systems like Git and CI/CD pipelines.

Soft Skills:
• Excellent problem-solving and analytical skills.
• Strong communication skills to convey technical concepts to non-technical stakeholders.
• Leadership and project management abilities.