> Markdown version of [/jobs/ext/2986607-data-scientist-iii](https://www.wearedevelopers.com/jobs/ext/2986607-data-scientist-iii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist III - **Company:** Mlops LLC - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $137,280.0 - $166,400.0 - **Contract:** Temporary to permanent - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data Infrastructure, Python (Programming Language), Machine Learning, Routing, Systems Development Life Cycle, Software Deployment, SQL Databases, Large Language Models, Snowflake, Generative AI, Information Technology, Machine Learning Operations, Virtual Agents, Software Version Control - **Published:** September 18, 2026 - **Apply:** https://mondo.gosnaphop.com/jobs/l/login/c8336608-98ca-11ec-8029-42010a8a0008/903f13ac-b3c8-11f1-9a74-024201c20d84/false?applyId=b0300610-b077-11f1-bc01-02420a6c7775&apply=true&returnUrl=%2Fjobs%2Fl%2Frecruiting%2Fjobapplication%2Fb0300610-b077-11f1-bc01-02420a6c7775%2F903f13ac-b3c8-11f1-9a74-024201c20d84%2Ffalse%3Fstep%3D1 ## About the Role Master's degree in a STEM field such as Mathematics, Computer Science, Statistics, or Engineering 5 years of experience as a Data Scientist with demonstrated longevity in recent roles, no frequent job changes 4 years of experience with Python and SQL, including complex statistical analysis and machine learning model development 3 years of MLOps experience, including building, deploying, and maintaining models through a full development lifecycle Background in GIS or geospatial analytics, with experience working with location-specific, transportation, or logistics data Experience with at least one cloud or data platform environment, AWS, Azure, or Snowflake Proficiency with Git for version control Preferred Qualifications: Hands-on experience with both Snowflake and AWS in a production environment Experience with Generative AI tools, agentic frameworks, or LLM-based applications Background in startup or high-growth environments with a self-starter mindset Familiarity with route optimization or logistics-focused machine learning problems Experience working directly with business stakeholders to translate analytical outputs into operational decisions *, Master's degree in a STEM field such as Mathematics, Computer Science, Statistics, or Engineering 5 years of experience as a Data Scientist with demonstrated longevity in recent roles, no frequent job changes 4 years of experience with Python and SQL, including complex statistical analysis and machine learning model development 3 years of MLOps experience, including building, deploying, and maintaining models through a full development lifecycle Background in GIS or geospatial analytics, with experience working with location-specific, transportation, or logistics data Experience with at least one cloud or data platform environment, AWS, Azure, or Snowflake Proficiency with Git for version control Preferred Qualifications: Hands-on experience with both Snowflake and AWS in a production environment Experience with Generative AI tools, agentic frameworks, or LLM-based applications Background in startup or high-growth environments with a self-starter mindset Familiarity with route optimization or logistics-focused machine learning problems Experience working directly with business stakeholders to translate analytical outputs into operational decisions ## Description This role supports the client's data and analytics team by building, deploying, and operationalizing machine learning models, geospatial solutions, and AI-driven architectures that optimize logistics and operational outcomes., Design and deploy end-to-end machine learning and AI models in cloud environments, including geospatial and route optimization use cases involving latitude and longitude data Build and scale RAG solutions and autonomous AI agents using Generative AI and agentic architecture frameworks Apply MLOps practices to manage the full model development lifecycle from experimentation through production deployment Conduct advanced statistical analysis including multivariate regression, logistic regression, cluster analysis, and decision trees on large datasets Develop and maintain analytical solutions for commercial and operational topics such as pricing optimization, customer segmentation, and logistics analytics Collaborate with stakeholders across the organization to communicate findings, model outputs, and recommendations clearly Embed Responsible AI principles across model development, deployment, and governance workflows ## Related Videos - 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