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Develops and maintains a government Investment Data Warehouse platform with AI/ML and GenBI capabilities, focusing on data modeling, ETL pipelines, and analytics dashboards using Snowflake, AWS, and React.
The Front-End/Full-Stack Developer will build and maintain analytics dashboards and AI-driven data warehouse solutions for public sector clients. The role focuses on UI/UX design, GenAI integration, and data visualization using technologies like React, Streamlit, Chainlit, and cloud-based AI services.
The Solution Architect will design and advance an Investment Data Warehouse platform, integrating Generative AI, machine learning, and automated decision-making tools within AWS and Snowflake ecosystems. The role involves technical leadership, prompt engineering, and building scalable, secure data pipelines for public sector clients.
The Advanced Analyst II develops and applies advanced machine learning and statistical models to solve complex business problems across retail operations, merchandising, and supply chain. The role involves partnering with stakeholders to deliver data-driven insights using technologies like Python, Azure, and Power BI.
Job Description: At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients,…
Builds and deploys predictive models for underwriting, pricing, claims, and customer retention using Python, SQL, and ML libraries while collaborating with actuarial and product teams to solve business problems.
Leads the design, development, and operation of full-stack, cloud-native software systems with AI integration for government/cybersecurity products, focusing on scalability, reliability, and automation.
This role involves developing and deploying software tooling for space environment testing, including hardware integration test code and proprietary MBSE software. The position requires proficiency in LabVIEW and Python, with a focus on test automation and hardware driver development.
The Machine Learning Engineer will design, build, and deploy production-grade machine learning and GenAI systems, including LLM integration and RAG pipelines. The role involves working across the full ML lifecycle, from data exploration and model training to MLOps and cloud-based deployment on AWS.
Develop, integrate, deploy, and maintain machine learning software solutions for US government missions using Python, Bash, and Linux within a Federal Solutions team.
Ensure SSD firmware quality by developing validation strategies for NVMe features, performing root-cause analysis, and enhancing test automation and CI/CD workflows using Python and AI-assisted tools.
Senior Data Scientist building end-to-end production decision systems—forecasting, optimization, pricing, and batch/real-time recommendations—using Python, PyTorch/TensorFlow, and SQL at a lottery and sports-betting company in Toronto.
Job Title: Distribution Ops & Planning Engineer III Location: Knoxville, TN Job Summary and Description: Utilities around the world are transforming their distribution systems to support electrification,…
Apply machine learning to sequence-function problems in mRNA therapeutics research, building models and algorithms for RNA/LNP design using Python's scientific stack, Bayesian optimization, and active learning.
Build and run machine learning models that turn high-volume security telemetry into accurate, low-noise detections for SoFi’s SOC and fraud teams, using Python, SQL, Spark, and cloud data platforms.
Works on the Border Wait Time project, preparing traffic congestion datasets, developing ML models to predict traffic volumes, and deploying solutions with Google Vertex AI. Core technologies include Python, TensorFlow/PyTorch/scikit-learn, and Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage).
Supports the creation and development of AI/ML solutions, builds prototypes using Generative AI and Large Language Models, prepares and analyzes data, and collaborates with teams. Core technologies include Python, Generative AI, LLMs, and cloud platforms like Azure/AWS/GCP.
Leads data science initiatives for global clients, designing ML models, deploying solutions on AWS, and mentoring teams to deliver measurable business value through end-to-end analytics.
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