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Title: AI/ML Data Scientist
Location: Phoenix, AZ - (100% Onsite)
Duration: 6 months (possibility of an extension)
JD:
Position Overview
Title: AI/ML Data Scientist
Location: Phoenix, AZ - (100% Onsite)
Duration: 6 months (possibility of an extension)
JD:
Position Overview
- We are seeking a highly experienced Senior Data Scientist to support and enhance our AIOps (Artificial Intelligence for IT Operations) solution. This position plays a critical role in advancing our anomaly detection, root cause analysis, and intelligent automation capabilities across enterprise systems.
- The ideal candidate will bring deep expertise in machine learning, statistical modeling, and large-scale data analysis, with strong hands-on proficiency in Python and SQL. This individual will drive innovation in operational intelligence by leveraging anomaly detection, causal reasoning, time series modeling, and emerging GenAI techniques.
- Design and implement scalable machine learning models for AIOps use cases including anomaly detection and root cause analysis.
- Develop and optimize advanced anomaly detection algorithms for infrastructure, application, and operational telemetry data.
- Apply causal reasoning frameworks to identify drivers of incidents and operational disruptions.
- Build and deploy time series forecasting and modeling solutions to predict performance degradation and system failures.
- Develop robust data pipelines and analytical workflows using Python and SQL.
- Integrate Generative AI (GenAI) techniques for intelligent summarization, incident triage, knowledge extraction, and automation.
- Collaborate with engineering, DevOps, and platform teams to operationalize ML models in production environments.
- Drive continuous improvement of model performance, scalability, and reliability.
- Mentor junior data scientists and contribute to best practices in MLOps and model governance.
- 6 years of experience in data science or applied machine learning roles.
- Strong communication and stakeholder management skills.
- Strong proficiency in Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow or similar).
- Advanced SQL skills for data manipulation and analysis.
- Proven experience in anomaly detection techniques (statistical, ML-based, deep learning-based).
- Strong understanding and practical application of causal inference and causal reasoning methodologies.
- Hands-on experience with large-scale structured and time series datasets.
- Solid knowledge of time series modeling (ARIMA, Prophet, LSTM, state-space models, etc.).
- Experience deploying models into production environments.
- Strong analytical thinking and problem-solving capabilities.
- Experience in AIOps, IT Operations analytics, or observability platforms.
- Exposure to GenAI / LLM-based solutions for operational intelligence.