Data Scientist AI/ML
Data Scientist AI/ML
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Salary Not Disclosed
1 Vacancy
Job Description
Location: Chicago IL
Domain: Aerospace
Long Term Contract
Looking for W2 Candidates. No C2C
Strategic AI Leadership: Translate complex business challenges into clear actionable AI/ML strategies and comprehensive technical roadmaps ensuring alignment with organizational goals.
Team Leadership & Mentorship: 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.
End-to-End Solution Delivery: Oversee the entire machine learning lifecycle from problem definition and data exploration to model design training validation deployment monitoring and ongoing optimization.
Production Deployment: Lead the successful deployment of robust scalable and high-impact ML solutions into production environments ensuring they generate measurable and significant business value.
Technical Excellence & Best Practices: Champion MLOps best practices ensuring robust model governance versioning testing and monitoring for all AI solutions.
Technology Evaluation & Integration: 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.
Stakeholder Collaboration: Collaborate effectively with cross-functional teams including engineering product and business units to understand requirements manage expectations and ensure successful project delivery.
Ethical AI Development: Apply a strong understanding of ethical AI principles fairness transparency and data privacy throughout the design development and deployment of all AI solutions.
Qualifications:
Experience: 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.
Technical Proficiency:
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.
Proficiency with version control systems particularly Git.
Experience with both SQL and NoSQL databases.
Familiarity with AI/ML specific tools and platforms such as OpenAI APIs and integration platforms like WSO2 for AI service orchestration.
Tarun K
Phone: 1-
Employment Type
Full-time
