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Cisco Data Scientist People Policy & Purpose 3P United States, Georgia, Atlanta 979406646
05.02.2025
The application window is expected to close on: Feb 28, 2025.Note: This job posting may close earlier if the position is filled or if a sufficient number of applications are received.
Your Impact
As aData Scientist/AI Engineerin the 3P Organization, you will play a pivotal role in:
- Enhance and maintain scalable, reliable data analytics pipelines.
- Build, deploy, and monitor AI learning agents to personalize and adapt Cisco Networking Academy learning experiences.
- Integrate advanced ML models into production to deliver insights, optimize workflows, and drive business transformation.
- Collaborate across teams to align AI initiatives with organizational goals, fostering innovation in learning and development.
Key Responsibilities
- Perform statistical analysis (e.g., hypothesis testing, regression, time-series modeling) to derive insights.
- Clean and preprocess datasets, handle missing data, outliers, and manage real-time data streams.
- Build, train, and deploy ML and deep learning models (e.g., CNNs, RNNs, transformers) for tasks like NLP, topic modeling, clustering, and anomaly detection.
- Design and maintain end-to-end AI pipelines with CI/CD integration and robust monitoring.
- Collaborate with teams to integrate AI/ML models via APIs using frameworks and libraries and implement scalable deployment on containerized environments (e.g., Docker, Kubernetes).
- Manage large-scale datasets using big data tools and distributed computing frameworks.
- Ensure monitoring and performance optimization of deployed models, utilizing cloud-based AI/ML solutions (Google Vertex AI, Azure Machine Learning or OpenAI, AWS SageMaker).
Minimum Qualifications
- Bachelor’s degree with 7+ years of experience, Master’s degree with3+ years of experience, or PhD with1+ year of experiencein Computer Science, Data Science, Statistics, or related fields
- Demonstrated experience in advanced statistical methods, including hypothesis testing, regression analysis, and time-series modeling.
- Demonstrated experience in SQL, database management and data warehousing to include familiarity with ETL process for managing large datasets.
- Demonstrated experience withVersion control toolslikeGit/GitHub
- Demonstrated experience with APIs and integrations to include building and consuming RESTful APIs.
- Demonstrated experiencedeploying AI/ML models usingcontainerized environments(e.g., Docker, Kubernetes)
Preferred Qualifications
- Programming:Familiarity with Golang for performance-critical applications and knowledge of R, Julia, MATLAB or similar for advanced statistical computations.
- AI and ML Expertise:
- Proficiency in frameworks (Scikit-learn, TensorFlow, PyTorch) for building and deploying ML models.
- Strong knowledge of ML algorithms (e.g., SVMs, decision trees, gradient boosting, ensemble methods).
- Familiarity with pre-trained tools (Hugging Face) and transfer learning for customized applications.
- NLP and Text Analytics:
- Experience with SpaCy, NLTK, Gensim, transformers, and advanced NLP techniques (e.g., text preprocessing, sentiment analysis, clustering, anomaly detection).
- Expertise in advanced language models for multilingual or domain-specific tasks.
- Cloud-Based ML Tools:
- Hands-on experience with Google Vertex AI, Azure ML, or AWS SageMaker for managing pipelines.
- Big Data and Workflow Automation:
- Proficient in ETL processes and CI/CD workflows for streamlined production and automation.
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