Top Senior Data Science Jobs in Kansas City, MO

Design and implement advanced ML models for real-time forecasting and decision support, ensure data provenance and lineage, integrate federated geospatial and multi-format data, produce ROM and quarterly cost/resource reports, and apply Agile sprint practices to deliver mission-aligned analytics for DoD/IC customers.

Build, ship, and own end-to-end ML models for vendor matching, order routing, and supply-chain optimization. Partner with data engineering to productionize models, quantify impact, document work, and implement decision logic components toward agentic AI in a fast-moving healthcare startup environment.

Lead development of time-series and econometric models (ARIMA, VAR, state-space, WLS, panel data) and Bayesian probabilistic frameworks. Use causal inference and stochastic processes to produce actionable insights, work with large datasets on Databricks, communicate results to stakeholders, and mentor junior team members.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

Design, build, and deploy production-grade generative AI applications: orchestrate multi-agent systems, implement advanced RAG with vector DBs, fine-tune and host LLMs, optimize GenAI workflows, and deliver scalable FastAPI-based backend services with Docker and monitoring.

Design, build, and deploy production-grade generative AI systems: multi-agent orchestration, advanced RAG with vector databases, integrate/swap LLMs, fine-tune models, optimize prompts and latency, and containerize services with monitoring and CI/CD.

Design, build, and scale production Generative AI systems: multi-agent orchestration, advanced RAG with vector databases, LLM integration and fine-tuning, scalable FastAPI backends, Dockerized deployment, monitoring, and GenAI optimization for latency, cost, and reliability.

Design, build, and deploy production Generative AI applications: orchestrate multi-agent workflows, implement advanced RAG with vector DBs, integrate and fine-tune LLMs, develop scalable FastAPI/async backends, containerize with Docker, and optimize GenAI systems for latency, cost, and reliability.

Lead research defining fabric's AI shopping roadmap: design and run quantitative studies, build models and benchmarks for AI search (AEO/GEO), run experiments, translate findings into customer-facing insights, and publish research to influence product and go-to-market strategy.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Develop, validate, and deploy statistical and machine learning models on large structured and unstructured tax datasets to detect fraud, prioritize audits, and score compliance risk. Clean and explore data, perform feature engineering, collaborate with stakeholders, and present technical findings to diverse audiences.

Develop, validate, and deploy predictive and statistical models on large tax and financial datasets to detect fraud and non-compliance. Perform data exploration, feature engineering, and model evaluation using Python/R, SQL, and Databricks. Collaborate with government clients and cross-functional teams, deliver technical and non-technical briefings, and ensure models are explainable, defensible, and maintainable in secure government environments.

Design and validate clinical and biomarker data pipelines, perform source-to-target mappings (e.g., EHR to data model), extend ontologies and vocabularies, ensure data quality, evaluate informatics tools, and support data architecture and analysis workflows for a regulatory-grade platform.

The Senior Data Scientist will analyze customer data, design experiments, build models, and support data-driven decision-making across product, marketing, and customer experience teams.

Lead retention and churn efforts by building survival and lifecycle-state models, classifying churn reasons, creating personalized win-back and next-best-action interventions, optimizing offers/promos, designing uplift experiments, and owning production model lifecycle, monitoring, and MLOps across Product, CRM, Marketing, and Engineering.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Design, evaluate, and productionize generative AI/ML solutions (RAG, agents, embeddings, retrieval). Build evaluation frameworks for hallucination detection, benchmark LLMs, optimize prompts/models, create datasets, fine-tune models, and collaborate to deploy and monitor enterprise-scale GenAI systems.

Lead and build KLDiscovery's gen-AI architecture and core systems. Design and implement LLMs, agents, RAG, vector search, embeddings, model selection, MLOps, telemetry, and evaluation harnesses. Ship high-impact prototypes and production components, mentor senior engineers, and represent AI strategy to product, customers, and partners.

Design and evaluate predictive and generative models, extract insights from disparate clinical and product data, build and partner on data pipelines, run rigorous evaluations and experiments, and deliver time-sensitive ad hoc analyses to product, engineering, and clinical stakeholders.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead design and ownership of ZoomInfo's PLG measurement system, define KPIs and leading indicators, analyze end-to-end customer journeys, diagnose growth issues, and influence product investments. Build AI-native, automated analytics workflows, reporting, and monitoring while partnering cross-functionally to prioritize experiments and scale insights that drive adoption, retention, monetization, and expansion.

Design, build, and deploy ML models across diverse use cases; work with managed cloud ML platforms and containerized solutions; collaborate with engineers on production integration and MLOps best practices; preprocess and analyze large datasets; mentor teammates and influence technical direction; translate complex ML concepts for technical and non-technical stakeholders.

As a Senior Data Scientist, you'll optimize search relevance, retrieve content, analyze data, and collaborate with teams to enhance product strategies.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

Design, develop, and deploy time-series and machine-learning forecasting models (ARIMA, SARIMA, ETS, XGBoost, LightGBM) for demand planning, inventory, and sales forecasting. Perform large-scale SQL data processing, operationalize models in cloud environments (Azure preferred), present insights, and lead client workshops.