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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/Data Science Eng I - **Company:** USA, UTILITIES SERVICES ALLIANCE, INC. - **Location:** Seattle, WA, United States - **Experience:** Starter - **Salary:** $71,000.0 - $121,000.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Big Data, BigQuery, Cloud Computing, Cloud Engineering, Cloud Storage, Software Quality, Databases, Continuous Integration, Data Governance, Extract Transform Load (ETL), Data Presentation, Data Visualization, Data Warehousing, Cursor (Graphical User Interface Elements), Programming Tools, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, NumPy, Query Optimization, Power BI, Tensorflow, Azure Machine Learning, Software Engineering, Statistical Process Control (SPC), SQL Databases, Computational Statistics, Tableau (Software), Cloud Platform System, GitHub Copilot, Pytorch, Flask (Web Framework), Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, Generative AI, Git, Fastapi, Pandas, Matplotlib, AI Platforms, Scikit Learn, Kubernetes, Information Technology, HuggingFace, Plotly, Machine Learning Operations, Tools for Reporting, Virtual Agents, Api Design, Restful APIs, Meditech, Azure Synapse Analytics, Software Version Control, Data Pipelines, Serverless Computing, Docker, Databricks, Microservices - **Published:** September 25, 2026 - **Apply:** https://startup.jobs/ai-data-science-eng-i-usa-minimed-distribution-cor-10173909 ## About the Role * Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or related field and 0 years of experience., * Hands-on experience in data science, AI/ML, or related roles. * Python: Proficient in Python for data science and analytical development, including pandas, NumPy, and data visualization libraries (matplotlib, seaborn, plotly) * AI/ML: Foundational experience building and evaluating ML models using scikit-learn, PyTorch, or TensorFlow * Cloud: Hands-on experience working with cloud platforms (AWS, Azure, or GCP) - e.g., cloud storage, compute, serverless functions, or managed ML services * SQL: Proficiency in SQL - joins, aggregations, filtering, and basic query optimization * Software Engineering: Understanding of software engineering fundamentals - version control (Git), code modularity, testing, and CI/CD concepts * Statistics: Working knowledge of foundational statistical concepts - hypothesis testing, distributions, regression, and sampling methods applied to real-world datasets * Communication: Ability to translate technical findings into clear, actionable insights for cross-functional audiences * LLMs / Generative AI: Familiarity with large language model APIs (OpenAI, Anthropic, etc.), prompt engineering, or building LLM-powered data workflows - strongly preferred * AI Dev Tools: Active use of AI-assisted coding environments such as Windsurf, GitHub Copilot, or Cursor as part of the daily development workflow - strongly preferred * Cloud Deployment: Hands-on experience containerizing and deploying models using Docker, Kubernetes, or cloud-native ML services (SageMaker, Azure ML, Vertex AI) - strongly preferred * Agentic AI Stack: Familiarity with tools and frameworks used to develop, orchestrate, and monitor agentic AI systems, including: + Agent frameworks (e.g., LangGraph, AutoGen) + Model, retrieval, and memory tooling (e.g., Hugging Face Transformers, Pinecone) + Evaluation, guardrails, and observability (e.g., LangSmith, Ragas) * MCP (Model Context Protocol): Awareness of or hands-on experience with MCP to connect AI models to external tools, databases, or APIs * API Development: Experience building REST APIs or microservices using FastAPI, Flask, or similar frameworks to serve ML models or data products * Data Warehousing: Exposure to platforms such as Snowflake, Databricks, BigQuery, or Azure Synapse * Advanced Statistics: Familiarity with multivariate analysis, survival analysis, or statistical process control (SPC) * BI Tools: Exposure to Power BI, Tableau, or similar dashboard and reporting platforms * Data Storytelling: A passion for turning complex data into compelling narratives that drive action * Medtech / Healthcare: Experience or genuine interest in medical technology, clinical studies, or healthcare data ## Description This AI/Data Science Engineer I role is focused on delivering intelligent analytics and AI-powered solutions that turn complex data into actionable insights and drive better decisions across the organization. This role blends applied data science with modern AI engineering practices, and the ideal candidate is a curious, technically strong data scientist who brings solid Python and analytical foundations, can build and deploy end-to-end solutions in cloud environments, and is eager to leverage cutting-edge AI tools to accelerate impact. Responsibilities may include the following and other duties may be assigned. * Partner with engineers and scientists to design, build, and deploy AI-powered applications and analytical pipelines that translate complex datasets into actionable insights * Develop, deploy, and maintain machine learning models and AI services to cloud environments (AWS, Azure, or GCP), including API development and model serving infrastructure * Write clean, production-quality Python code and build SQL-based data models across cloud data warehouse environments, including ETL/ELT pipeline development * Prototype and iterate on ML models (classification, regression, anomaly detection, NLP) to support predictive analytics use cases * Actively leverage AI-assisted development tools (e.g., Windsurf, GitHub Copilot, Cursor) to improve development velocity, code quality, and solution design * Communicate findings clearly to both technical and non-technical stakeholders through polished visualizations, reports, and presentations * Contribute to data and AI infrastructure strategy, including schema design, data governance, and cloud architecture best practices ## Related Videos - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [Vectorize all the things! 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