St. Louis, MO

Data Jobs in St. Louis, MO

19 jobs found

Include remote jobs

Today

Data Scientist III

Centene St. Louis, MO

St. Louis, MO

Today

$108k - $199k/yr Full time Advanced Analytics Artificial Intelligence Big Data

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Job Description

Centene is hiring a Data Scientist III for an onsite role in Missouri, supporting Ambetter membership forecasting and reporting. In this position, you will develop predictive models, analytic frameworks, and data products that support financial planning, pricing, and strategic decision-making while accounting for regulatory, competitive, operational, and product-level changes.

What you will do

Design and build data models that predict member outcomes or the future impact of key member decisions
Design, develop, validate, and maintain machine learning and statistical models, including forecasting methodologies for Marketplace membership and related business outcomes
Build and manage data assets, feature engineering pipelines, and analytical datasets that power forecasting and reporting
Perform exploratory analysis to spot emerging trends, structural market shifts, and business drivers that affect forecast performance
Design and construct analysis tools to extract and analyze data, and store analytical results in formats aligned to business needs
Conduct exploratory data analysis from complex data sources to create key datasets in support of Centene’s mission
Evaluate and design experiments to monitor key metrics and identify opportunities to improve outcomes
Develop mathematical and statistical models to identify relevant content or events and recognize patterns
Present research findings and communicate results of analysis
Contribute to automated, operational analytics processes that support scale and durability of analysis
Validate and measure health management program outcomes using SAS, R, and other tools, including provider, claims, and membership data
Manage multiple projects as assigned and help train Data Analysts
Support technical team liaisons across business requirements gathering, documentation, testing, delivery, and user adoption for Health Plan initiatives

Required qualifications

Authorization to work in the U.S. without employment-based visa sponsorship now or in the future
No sponsorship available, including H-1B, L-1, O-1, H-1B1, F-1, J-1, OPT, or CPT
Master’s degree in Statistics, Mathematics, Computer Science, Informatics, Econometrics, Engineering, or Experimental Science with 5+ years of experience, or a Bachelor’s degree with 7+ years of quantitative analysis experience in data science capabilities such as data mining, predictive modeling, machine learning, statistical modeling, large-scale data acquisition, transformation, and analysis of structured and unstructured data
Experience with database technologies including Teradata, MS SQL Server, and Snowflake

Preferred skills

R, Python, SQL, Databricks, Snowflake, Posit, and JupyterHub

Tools and technologies

R, Python, SQL
Databricks, Snowflake
Posit, JupyterHub
SAS, Teradata
MS SQL Server

Compensation and benefits

Competitive pay: USD 107,700 - 199,300 per year
Health insurance
401K and stock purchase plans
Tuition reimbursement
Paid time off plus holidays
Flexible approach to work with remote, hybrid, field, or office work schedules

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Today

AI Engineer Consultant

Deloitte St. Louis, MO

St. Louis, MO

Today

Full time Backend Developer Ai Engineer Artificial Intelligence

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Job Description

Deloitte is hiring an AI Engineer Consultant for onsite AIOps/MLOps engineering in a Azure + Databricks environment under its Project Delivery Talent Model.

Responsibilities

Monitor Databricks jobs and clusters by tracking job run status, cluster utilization, and auto-scaling behavior via Databricks Jobs UI and Azure Monitor, resolving failed or delayed pipeline runs.
Build and maintain CI/CD pipelines in Azure DevOps using YAML, deploying notebooks, ML models, and Databricks workflows across dev/staging/prod with Databricks Repos and Git integration.
Manage the MLflow model lifecycle: track experiments, register and version models in the MLflow Model Registry, and handle transitions for staging and production along with lineage.
Maintain Delta Lake pipelines by enforcing data quality, schema standards, and ACID compliance across bronze/silver/gold layers for training and inference workloads.
Monitor model performance and drift by setting up automated drift detection (data and concept drift) using Databricks native monitoring or custom Azure ML integration, triggering retraining when thresholds are breached.
Optimize compute and cost by configuring Databricks clusters (job clusters vs. all-purpose), leveraging autoscaling and spot instances, and using Azure cost management dashboards to control spend.
Implement observability using Azure Monitor and Log Analytics with end-to-end logging and alerting across Databricks, Azure ML, and downstream services via Application Insights and Log Analytics workspaces.
Support security, access, and governance by configuring Unity Catalog for data and model governance, managing service principals, secrets via Azure Key Vault, and RBAC across workspaces.
Collaborate on deployment using Azure ML endpoints, deploying models as real-time or batch endpoints via Azure ML Managed Endpoints or Databricks Model Serving, focused on scalability and low-latency inference.
Provide on-call support and incident response: troubleshoot pipeline failures, cluster crashes, or endpoint downtime; perform root cause analysis and post-incident reviews to improve pipeline resilience.

Requirements

3-6+ years of experience in DevOps/MLOps/Data Engineering, including 1-2 years hands-on with Databricks and Azure.
Strong proficiency in Python and/or Scala, plus SQL for data transformation and querying.
Hands-on experience with Databricks components: Jobs, Workflows, Unity Catalog, Delta Lake, and Databricks Model Serving.
Proficiency in the Azure ecosystem: Azure DevOps, Azure ML, Azure Monitor, Azure Key Vault, and Azure Data Factory.
Experience with MLflow for experiment tracking and model registry management.
Working knowledge of CI/CD practices and Infrastructure as Code using Terraform or ARM/Bicep templates.
Understanding of ML lifecycle concepts: model training, validation, deployment, monitoring, and retraining.
Education: Bachelor's degree, preferably in Computer Sciences, Information Technology, Computer Engineering, or a related IT discipline.

Technical tools

Azure, Databricks, Azure Monitor, Databricks Jobs UI, Azure DevOps
YAML, Databricks Repos, Git, MLflow, MLflow Model Registry
Delta Lake, Databricks native monitoring, Azure ML, Databricks clusters, autoscaling, spot instances
Application Insights, Log Analytics workspaces, Unity Catalog, service principals, Azure Key Vault, RBAC
Azure ML Managed Endpoints, Databricks Model Serving, Python, Scala, SQL, CI/CD
Infrastructure as Code, Terraform, ARM, Bicep, Azure Data Factory

Additional information

Limited immigration sponsorship may be available.
Travel: 10% on average, including potential overnight travel.

Preferred

Familiarity with containerization (Docker) and orchestration (Kubernetes, if applicable).
Analytical ability to manage multiple projects and prioritize tasks into manageable work products.
Can operate independently or with minimum supervision.
Excellent written and communication skills.
Ability to deliver technical demonstrations.

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26d ago

Data Engineer

D&G Support Services, LLC St. Louis, MO

St. Louis, MO

26d ago

$125k - $150k/yr Full time Backend Developer Azure Big Data

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Job Description

At D&G Support Services, LLC, this on-site Data Engineer role supports USTRANSCOM’s mission as the Single Manager for Global Bulk Fuel Management and Delivery (GBFMD). You will help establish and maintain the foundational data capabilities for the Joint Petroleum Enterprise (JPE), enabling bulk fuel data collection, management, and consumption across the Department of Defense through pipelines, APIs, and integration solutions.

What you will do

Develop and maintain data pipelines that ingest data into Databricks and support integration with Palantir Ontology and other enterprise platforms.
Work with cross-functional teams to support Common Operating Picture (COP) development and related data integration activities.
Review and analyze Joint Petroleum Enterprise data sources, including applications, websites, programs, and operational systems, to identify data integration and enhancement opportunities.
Design and implement scalable ingestion processes that transform source data into structured formats for enterprise consumption and API development.
Develop, publish, and maintain APIs that provide standardized access to enterprise data across the Joint Petroleum Enterprise.
Collaborate with stakeholders to manage and maintain enterprise data dictionaries, metadata repositories, and data governance artifacts.
Administer data structures, data topics, and engineering processes, applying industry best practices.
Participate in technical working groups and stakeholder meetings to support metadata requirements, data modeling, architecture decisions, and tool selection.
Support preparation of presentations and technical materials for USTRANSCOM, Joint Staff, and Office of the Secretary of Defense governance forums.
Provide technical recommendations and support for enterprise data modernization initiatives.
Complete additional assigned projects and tasks as directed by program leadership.

Required qualifications

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
5+ years of experience in data engineering, software development, or a related technical discipline.
Strong proficiency with SQL and Python.
Experience building and maintaining data pipelines using Apache Spark, Kafka, or similar technologies.
Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
Experience designing and implementing data integration solutions.
Ability to communicate effectively with technical and non-technical stakeholders.
Active Secret clearance with eligibility to obtain and maintain a TS/SCI.

Preferred experience

Experience with Databricks and Palantir Ontology.
Experience with data warehousing, ETL processes, and enterprise data management.
Experience with API development and RESTful web services.
Experience with data modeling techniques and metadata management.
Experience with Maven Smart Systems or similar logistics and supply chain platforms.
Experience supporting the Department of Defense, Defense Logistics Agency (DLA), or USTRANSCOM.
Experience working in Agile development environments.

Technologies

SQL, Python, Databricks
Palantir Ontology
Apache Spark, Kafka
AWS, Microsoft Azure, Google Cloud Platform

Compensation and benefits

USD 125,000 - 150,000 per year
Competitive salary
Benefits
401(k)
Bonus and profit sharing
Flexible hours
Education reimbursement
PTO

Eligibility and location

Secret clearance with ability to obtain and maintain TS/SCI
Travel within CONUS up to approximately 10%
Restricted to U.S. persons as defined under 8 U.S.C. 1324b(a)(3)
On site at Scott Air Force Base, Illinois

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1mo ago

Research/Data Analyst

State of Missouri St. Louis, MO

St. Louis, MO

1mo ago Closed

$65k - $65k/yr Full time Data Analysis Data Analytics HR

This position is no longer accepting applications (closed Sep 12, 2026).

Job Description

The Department of Social Services Children’s Division is hiring a senior-level Research/Data Analyst to support research, analysis, and statistical interpretation across recruitment and retention topics.

Analyze and track employee turnover using exit interview review, focus groups, additional data collection methods, and analysis of relevant datasets
Develop, review, and analyze customer service feedback, including program grievances and related trends
Collaborate with internal and external partners across all levels of the division to obtain information, clarify data, and identify factors affecting reported data
Provide recommendations to improve organizational structure, operations, performance, practices, methods, policies, procedures, program outcomes, and service delivery aligned to organizational goals
Support goal setting and strategic planning activities
Perform other duties as assigned

Requirements

1+ years of experience as an Associate Research/Data Analyst with the Missouri Uniform Classification and Pay System
Bachelor’s degree from an accredited college or university with at least 24 earned credit hours in one or a combination of:
- Business or Public Administration
- Economics
- Finance
- Industrial Engineering
- Engineering Management
- Closely related field
2+ years of professional experience in management analysis, fiscal or financial analysis, operations research, or industrial engineering
Strong problem-solving and time management
Excellent communication skills (oral, written, and interpersonal)
Ability to travel throughout the State of Missouri as needed

Benefits

Defined pension plan
Generous leave and holiday time
Eligibility for health insurance coverage

Location

Base location depends on the selected candidate and office capacity
Internal promotional applicants are encouraged to apply due to potential alternate office space
Selected individuals may receive a higher rate based on a pay differential (for example, shift or time-of-service pay)

Compensation

USD 65,261 per year

Contact

For questions or accommodations related to applying or interviewing, email: CD-HR@dss.mo.gov

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1mo ago

Machine Learning Engineer

H&R Block St. Louis, MO

St. Louis, MO

1mo ago Closed

$91k - $146k/yr Full time Ai Ml Artificial Intelligence Data Science

This position is no longer accepting applications (closed Sep 12, 2026).

Job Description

Join H&R Block in Missouri (onsite) and apply machine learning to real business challenges, including generative AI. This role focuses on designing, building, and deploying models that can run reliably in production, supported by strong collaboration across engineering teams and MLOps.

Compensation: $91,000.00 - $145,600.00 per year. Local minimum wage laws apply, and individual pay decisions depend on job-related factors such as experience, education, skill, performance, and the geographic location where work is performed. Successful candidates may be eligible for one or more incentive compensation or short-term incentive plans, which could generate additional earnings based on plan terms.

What you’ll do

Design, build, and deploy machine learning models, including generative AI models, to address complex business problems.
Work with teammates to preprocess, clean, and analyze both structured and unstructured data for machine learning pipelines.
Tune and optimize models for accuracy, efficiency, and scalability in production environments.
Collaborate with MLOps Engineers to support deployment, monitoring, and maintenance of ML models.
Stay current on advancements in machine learning, deep learning, and generative AI, and apply them when appropriate.
Contribute to a collaborative engineering culture through knowledge sharing, code reviews, and support of team initiatives.

Required qualifications

Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience).
3 years total experience.
Hands-on experience with ML frameworks such as scikit-learn, TensorFlow, PyTorch, and spaCy.
Proficiency in Python and familiarity with ML development workflows.
Strong analytical and problem-solving skills with attention to detail.
Effective communication and collaboration in a team-oriented environment.
Experience with generative AI is a plus.

Preferred qualifications

Master’s or PhD in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience).
Hands-on experience building and deploying machine learning models for real time inference.

Tools you’ll work with

Python, scikit-learn, TensorFlow, PyTorch, spaCy

Benefits and support

Competitive pay and comprehensive benefits
Support for life both in and outside of work
Medical and prescription drug coverage for qualifying associates and/or eligible dependents
H&R Block Retirement Savings Plan (401(k) Plan)
Employee Assistance Program
(virtual) fitness center programs
Associate discount program
Associate Tax Prep benefit

Note: This posting includes required pay range information and may be subject to local requirements. Individual compensation and eligibility for incentives depend on job-related factors and plan terms.

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1mo ago

Senior Data Scientist - AI Trainer

DataAnnotation St. Louis, MO 🇺🇸 Remote

St. Louis, MO

1mo ago Closed

$50 - $100/hr Contract Senior Ai Trainer Artificial Intelligence

This position is no longer accepting applications (closed Sep 4, 2026).

Job Description

DataAnnotation is seeking a Senior Data Scientist - AI Trainer to support the training of AI models that reason with quantitative data. In this contract role, you will review AI-generated quantitative work, create and evaluate training and benchmarking tasks, and provide feedback that informs the next iteration of model behavior.

Key Responsibilities

Assess AI-generated quantitative outputs, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, focusing on technical accuracy and real-world validity.
Develop and solve quantitative problems used to train and benchmark AI systems, covering areas such as forecasting, experimental analysis, optimization, and statistical inference.
Produce clear technical explanations and well-documented analytical code to support evaluation and reuse.
Deliver feedback that directly influences the design and improvement of AI systems for quantitative reasoning.

Required Qualifications

3+ years of hands-on experience in a quantitative role or research environment (examples include data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a closely related field).
Some coding experience required, including comfort writing and reviewing analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
Fluency in English (native or bilingual level) with strong writing skills.
A bachelor’s degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); an advanced degree (Master’s or PhD) is a plus.
Relevant credentials are a plus, such as Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise.

Technologies

PayPal
AWS
GCP

Contract Benefits

Fully remote: eligible candidates can work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: select which projects to take on and when to work, using your own computer.
Competitive pay: projects are paid hourly at $50 to $100 USD per hour, with bonus rates available on some projects.
Impact: contribute to AI systems designed to reason about data and analytics.

Additional Notes

Payment is made via PayPal.
We will never ask for any money.
This role is available only to candidates located in the US, Canada, UK, Ireland, Australia, and New Zealand.

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1mo ago

Marketing Data Scientist - AI Trainer

DataAnnotation St. Louis, MO 🇺🇸 Remote

St. Louis, MO

1mo ago Closed

$50 - $100/hr Contract Marketing Ai Training Analytics

This position is no longer accepting applications (closed Aug 28, 2026).

Job Description

DataAnnotation is seeking a Marketing Data Scientist - AI Trainer for a contract role based in St. Louis, MO with remote work options. The position offers flexible scheduling and the opportunity to help train AI models that reason about data and analytics. You will evaluate AI-generated quantitative work, provide actionable feedback, and influence the next generation of quantitative AI systems.

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: select projects and set your own hours, using your own computer from home.
Competitive pay: hourly rates from USD 50 to 100, with bonus rates available on some projects.
Impact: help shape AI systems designed to reason about data and analytics.

Responsibilities

Evaluate AI-generated quantitative work for technical accuracy and real-world validity across statistical analysis, predictive modeling, scientific reasoning, and data-driven insights.
Design and solve quantitative problems used to train and benchmark AI systems, covering forecasting, experimental analysis, optimization, and statistical inference.
Produce clear technical explanations and well-documented analytical code.
Provide feedback that directly informs the next generation of AI models built for quantitative reasoning.

Requirements

3+ years in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or related fields.
Some coding experience required, with comfort writing and reviewing analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design (A/B testing, hypothesis testing, regression, classification, time-series forecasting).
Fluent English with strong writing skills.
Bachelor's degree in a quantitative field preferred; Master’s or PhD is a plus.
Relevant credentials are a plus (e.g., Kaggle competition ranking, AWS or GCP ML certifications, or equivalent demonstrated expertise).