Data Scientist/AI/ML Engineer with Agentic AI experience

Genuine Candidate with proper LinkedIn profile | Share Resume with Location and Visa | Need Passport number at the time of submission | Local to NY/NJ/CT/TX | ONSITE INTERVIEW

Role: Data Scientist/AI/ML Engineer with Agentic AI experience
Client: Cigna Health (Direct Client)

Location: Morris Plains NJ, Bloomfield CT, Austin, or Dallas TX

Duration: 12+ months

Work Type: Hybrid

Interview: Onsite Interview
Visa- All

Must have strong experience with Agentic AI

 

 

Primary Responsibilities:

• Lead the development and training of machine learning models.
• Optimize AI algorithms for performance, efficiency, and scalability.
• Design and implement robust and scalable data pipelines.
• Integrate AI systems with enterprise software and cloud-based applications.
• Drive data-driven decision-making by working with cross-functional teams.
• Plan and lead analytics projects, ensuring alignment with business goals.
• Present findings and insights to stakeholders, translating complex technical results into actionable business recommendations.
• Ensure quality and compliance of data and modeling results with business and regulatory requirements.
• Mentor and guide junior data scientists, fostering technical growth and best practices in AI/ML development.

Required Qualifications & Skills:

• At least 6 years of experience developing AI and ML solutions in a professional setting.
• Bachelor’s degree in computer science, Data Science, or a related field (Master’s preferred).
• Experience developing AI-driven chatbots using RAG and AI agents with LangChain.
• Advanced proficiency in Python and SQL for data science applications.
• Strong understanding of machine learning techniques, including supervised, unsupervised, and reinforcement learning.
• Expertise in deep learning architectures (CNNs, RNNs, Transformers) and NLP techniques.
• Proficiency in designing scalable and maintainable AI systems, including microservices and REST API development.
• Hands-on experience with cloud computing platforms such as AWS, Databricks, Azure, and GCP.
• Knowledge of MLOps best practices, including CI/CD pipelines, containerization (Docker, Kubernetes), and role-based access provisioning.
• Strong ability to communicate AI/ML insights and model performance to both technical and non-technical stakeholders.

Preferred Qualifications:

• Expertise in mathematical concepts, including statistics, probability, linear algebra, and calculus.
• Experience with distributed computing frameworks such as Apache Spark.
• Familiarity with advanced AI tools and platforms, including PyTorch, Hugging Face, and Kafka.
• Strong project management and leadership skills, with experience driving AI/ML initiatives in a business environment.
• System design expertise, ensuring scalability and robustness in AI deployments.