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Remote Data Scientist Risk Jobs in Missouri (NOW HIRING)

Koantek

Senior AI Engineer

Chesterfield, MO · Remote

$54.75 - $70.50/hr

Sr AI Engineer / Data Scientist / MLOps Consultant Location: United States - Remote Employment Type: Full-Time and Contract We are seeking an experienced and highly technical Data Scientist to join ...

Kohl's

$58.50 - $75.25/hr

Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent practical experience. * 7+ years of experience in data architecture, data ...

GRVTY

Imagery Scientist (EO) - Senior

Saint Louis, MO · On-site +1

$160K - $190K/yr

Assess potential differences in metadata, data format, and data structure characteristics in regard ... Remote sensing phenomenology * Image formation processes * Exploitation products and methodologies

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · Remote

$113K - $136K/yr

United States - Remote Employment Type: Full-Time and Contract Data Engineer Description: As a Data ... Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent ...

GRVTY

Imagery Scientist (EO)- Expert

Saint Louis, MO · On-site +1

$180K - $210K/yr

Data formats * APIs and ETL processes * Existing operational pipelines * Develop strategies to ... Remote sensing phenomenology * Image formation processes * Exploitation products and methodologies

Relativity

Principal Applied Scientist

California, MO · On-site +1

Remote/Hybrid Job Overview Relativity is a leading legal data intelligence company building ... Applied Science Team The Applied Science team sits at the core of Relativity's AI development. We ...

Relativity

Principal Applied Scientist

Kansas City, MO · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Applied Science Team At Relativity, we are building a worldclass Applied Science organization ...

Kohl's

$112K - $148K/yr

Collaborate with stakeholders, data scientists, and full stack engineers to deliver trusted, documented, and reusable data products What Skills You Have Required * 4+ years of experience in software ...

Kohl's

$89K - $122K/yr

Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient ...

Jobgether

$49.25 - $63.25/hr

Bachelor's degree in Computer Science, Information Systems, or related field preferred, or ... Fully remote engagement with flexible working arrangements. * Opportunity to architect a next ...

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Remote Data Scientist Risk jobs near you
Infographic showing various Remote Data Scientist Risk job openings in Missouri as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Senior AI Engineer

Senior AI Engineer

Koantek

Chesterfield, MO • Remote

$54.75 - $70.50/hr

Contractor

Re-posted 7 days ago

Job description

Sr AI Engineer / Data Scientist / MLOps Consultant Location: United States - Remote Employment Type: Full-Time and Contract We are seeking an experienced and highly technical Data Scientist to join our customer-facing consulting team. This remote role requires a blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. The successful candidate will be instrumental in designing, deploying, and maintaining production-grade ML solutions, including advanced Generative AI and Natural Language Processing (NLP) models, for our diverse client base.Key Responsibilities Serve as a primary technical consultant, leading and executing end-to-end ML project implementations directly with clients, translating complex business problems into robust technical solutions

Exhibit excellent communication, presentation, and stakeholder management skills to clearly articulate technical findings, proposals, and project status to both technical and non-technical audiences. Design, build, and maintain production-grade ML pipelines, focusing on continuous integration, continuous delivery (CI/CD), and advanced MLOps practices to ensure reliability and scalability of models. Implement and optimize cutting-edge Generative AI and NLP applications, demonstrating hands-on experience with technologies like Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) in a production setting.

Manage underlying solution infrastructure, demonstrating proficiency in technologies such as Docker, pipeline orchestrators, and database systems. Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-performance data processing (e.g., using technologies like Apache Spark). Contribute to the strategic growth of the ML Practice Team, including participation in technical assignments and knowledge transfer activities

Ensure all client engagements and training activities are properly documented and reported via designated partner platforms. Required Qualifications 4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models in a live environment. 3+ years of experience in a customer-facing consulting or solutions architect role, focused on technical implementation and delivery.

Excellent verbal and written communication skills for effective client and internal team interaction. Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices. Demonstrable experience with infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.

Deep understanding of programming for data-intensive and scalable ML applications. Proven experience in deploying and managing Generative AI and NLP solutions for client applications. Preferred Qualifications Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing. Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures. Requirements Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing. Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.

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