AI And Data Analytics Engineer

Job Description

Job Title: AI and Data Analytics Engineer

Client: Cigna
Employment Type: Contract
Experience Required: 12+ Years
Location: Morris Plains, NJ | Dallas, TX | Florida (Hybrid/Onsite as applicable)

Job Summary

Cigna is seeking an experienced AI and Data Analytics Engineer to lead the design, development, and deployment of advanced AI and machine learning solutions. This role will play a critical part in driving data-driven decision-making, building scalable AI systems, and delivering impactful analytics aligned with business and regulatory requirements. The ideal candidate combines strong technical expertise with leadership, communication, and project management skills.

Key Responsibilities

• Lead the development, training, and deployment of machine learning and AI models.
• Optimize AI algorithms for performance, efficiency, scalability, and reliability.
• Design, build, and maintain robust, scalable data pipelines for analytics and ML workloads.
• Integrate AI/ML solutions with enterprise platforms and cloud-based applications.
• Collaborate with cross-functional teams to drive data-driven business decisions.
• Plan and lead analytics and AI projects, ensuring alignment with organizational goals.
• Translate complex analytical and modeling results into actionable insights for business stakeholders.
• Ensure data quality, model accuracy, and compliance with business, security, and regulatory standards.
• Establish and promote best practices in AI/ML development and deployment.
• Mentor and guide junior data scientists and engineers, fostering technical excellence and growth.

Required Qualifications & Skills

• 6+ years of professional experience developing and deploying AI and machine learning solutions.
• Bachelor’s degree in computer science, Data Science, Engineering, or a related field (master’s degree preferred).
• Advanced proficiency in Python and SQL for data science and analytics applications.
• Strong understanding of machine learning methodologies, including supervised, unsupervised, and reinforcement learning.
• Hands-on expertise with deep learning architectures such as CNNs, RNNs, and Transformers, as well as NLP techniques.
• Experience building AI-driven chatbots using RAG (Retrieval-Augmented Generation) and AI agents with LangChain.
• Proficiency in designing scalable AI systems, including microservices and RESTful APIs.
• Hands-on experience with cloud platforms such as AWS, Azure, GCP, and Databricks.
• Solid understanding of MLOps best practices, including CI/CD pipelines, containerization (Docker, Kubernetes), and role-based access provisioning.
• Strong communication skills with the ability to explain AI/ML concepts and results to both technical and non-technical audiences.

Preferred Qualifications

• Strong foundation in mathematics, including statistics, probability, linear algebra, and calculus.
• Experience with distributed computing frameworks such as Apache Spark.
• Familiarity with advanced AI/ML tools and platforms, including PyTorch, Hugging Face, and Kafka.
• Proven leadership and project management experience driving AI/ML initiatives in enterprise environments.
• System design expertise with a focus on scalability, performance, and robustness of AI solutions.