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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Data Scientist - **Company:** TALENTHOP LLC - **Location:** United States (Remote available) - **Experience:** Starter - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Information Systems, Data as a Services, Extract Transform Load (ETL), Data Mining, Apache Hadoop, Python (Programming Language), Machine Learning, Natural Language Processing, Open Source Technology, Tensorflow, SQL Databases, Unstructured Data, Workflow Management Systems, Enterprise Software Applications, Pytorch, Large Language Models, Prompt Engineering, Apache Spark, Model Validation, Generative AI, Scikit Learn, Information Technology, HuggingFace, Modeling and Simulation, AWS Glue, Apache Kafka, Data Management, Machine Learning Operations, Data Pipelines, Databricks - **Published:** September 27, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pmw19urtza ## About the Role * Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, Artificial Intelligence, Engineering, Information Systems, Operations Research, or related field. * 0-2 years of experience in data science, machine learning, AI, or advanced analytics. * Foundational experience with machine learning model development or evaluation. * Working knowledge of Python, SQL, Scikit-Learn, TensorFlow and/or PyTorch, Hugging Face or similar frameworks. * Experience with predictive analytics, statistical analysis, data mining, and model evaluation. * Experience with structured and/or unstructured datasets. * Exposure to Generative AI, Large Language Models, or prompt engineering. * Exposure to Retrieval Augmented Generation concepts or architectures. * Familiarity with cloud and data platforms such as AWS, Azure, GovCloud, Databricks, Apache Spark, Hadoop, Kafka, Airflow, or AWS Glue. * Ability to support AI/ML integration with APIs, workflow tools, enterprise applications, or data services. * Strong written and verbal communication skills. * U.S. Citizenship required. * Ability to obtain and maintain a DHS Public Trust. ## Description The AI/ML DATA SCIENTIST role contributes to the development and implementation of AI and data analytics solutions that support mission and business functions. This position aids in discovering use cases, assessing data readiness, building prototypes, and piloting models, working closely with multidisciplinary teams. The role is essential in advancing AI/ML applications that improve operational outcomes and decision advantages., * Support design, development, testing, and evaluation of AI/ML solutions for mission and business operations. * Assist in predictive, classification, anomaly detection, natural language processing, generative AI, and other analytical solution development. * Contribute to training, tuning, validation, and documentation of machine learning models. * Support AI-enabled MVPs, technical demonstrations, automation pilots, and rapid experimentation. * Research and assess commercial, government, and open-source AI/ML models and tools. * Conduct exploratory data analysis with structured and unstructured datasets. * Identify trends, patterns, anomalies, and insights to aid decision-making. * Assist in developing model baselines, performance measures, acceptance criteria, and testing methods. * Evaluate model accuracy, reliability, limitations, and operational suitability. * Develop dashboards, visualizations, and analytical summaries. * Follow established data science methods and team best practices. * Support data readiness assessments regarding availability, quality, completeness, lineage, ownership, and accessibility. * Clean, normalize, transform, and prepare data for AI/ML analysis. * Diagnose data-quality issues and document corrective actions. * Assist in developing data pipelines, ETL processes, and reusable datasets. * Help integrate data from various systems and platforms. * Collaborate with engineers to transition prototypes to scalable solutions. * Support automation assessments and pilot evaluations. * Assist in identifying AI/ML opportunities for workflow automation and digital transformation. * Support integration of AI/ML with enterprise platforms and tools. * Participate in business process analyses to reduce manual effort. * Support intelligent document processing and AI-assisted workflow improvements. * Aid mission modeling and simulation efforts for operational evaluation. * Assist in scenario planning, forecasting, experimentation, and trade-space analysis. * Translate analytical outputs into clear findings for diverse audiences. * Support data-driven decision-making aligning operational needs with analytics. * Collaborate on AI governance, security, privacy, and responsible AI use. * Document assumptions, methodologies, risks, and lessons learned. * Support authorization documentation and reviews. * Engage in Agile development activities and stakeholder collaboration. * Prepare technical documentation and stakeholder presentations. * Measure user adoption, operational impact, and efficiency gains. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Got AI ideas but no money? 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