Chameleon Integrated Services

AI/ML Technical Lead / Senior Data Scientist

Posted 2 Days Ago

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St Louis, MO, USA

In-Office

Senior level

Information Technology

The Role

Lead and implement three production AI/ML models using Army data (GCSS-Army, SAP ECC). Perform data exploration, feature engineering, model development, evaluation, deployment, monitoring, and retraining on Azure. Work with SMEs and MLOps engineers to integrate outputs into dashboards/Power Apps, prepare documentation/model cards, and support production-readiness reviews.

Summary Generated by Built In

We are a growing information technology company that offers its employees a culture of success, the chance to work on revolutionary federal IT infrastructure, and the opportunity to grow alongside cutting-edge technology that is reshaping the industry. We are seeking forward-thinking candidates that have strong experience in operational support and can help take to the next level in a proactive stance.

Chameleon Integrated Services has expertise in operations management, quality systems, data operations and cybersecurity. We secure some of the most sensitive data for the Department of Defense and for other U.S. federal government agencies. We are known for the great care we take with clients and employees, and we believe in promoting from within.

We offer a Full Benefits package including:

Competitive Employee Health Insurance options including dental
100% company paid vision plan
401K plan with generous company match and no vesting period
100% company paid life insurance
100% company paid long and short-term disability insurance
Training allowance
PTO and more

AI/ML Technical Lead / Senior Data Scientist
Role: Provide hands-on technical leadership for the three required AI/ML models using CASCOM, GCSS-Army, SAP, and other Army data. This person must be capable of coding, evaluating, deploying, and sustaining models—not merely leading strategy discussions.
The potential use cases include GenAI/OpenAI, Copilot, SAP ECC search, document extraction, anomaly detection, equipment-readiness forecasting, maintenance forecasting, fleet automation, and supply forecasting.
Requirements:

Active Secret clearance.
Hands-on production AI/ML development.
Strong Python and SQL capability.
Experience taking at least one model from requirements through production or operational deployment.
Experience with Azure-based AI/ML services or a comparable cloud environment.
Able to explain model evaluation, deployment, monitoring, and retraining.

Bachelor’s degree in computer science, data science, statistics, mathematics, operations research, engineering, or a related discipline; equivalent specialized experience may substitute.
Seven or more years in data science, machine learning, advanced analytics, or applied AI.
Four or more years developing machine-learning solutions.
Experience delivering at least three substantive models or AI capabilities, with at least one in production.
Strong Python, SQL, pandas, NumPy, scikit-learn, and one major ML or deep-learning framework.
Experience with two or more of the following:
- Forecasting.
- Anomaly detection.
- Classification.
- Recommendation engines.
- Optimization.
- Document extraction.
- NLP, RAG, or GenAI.
Experience defining measurable model-performance criteria.
Experience with feature engineering, training, validation, test data, error analysis, explainability, and model documentation.

Strong preferences

Azure Machine Learning, Azure OpenAI, Azure AI Search, Microsoft Copilot, or comparable Azure AI services.
Defense logistics, maintenance, readiness, fleet, supply chain, acquisition, property, or financial analytics.
GCSS-Army, SAP ECC, ERP, or maintenance-system data.
Classified or Government-cloud deployment.
Model monitoring, drift detection, bias testing, red teaming, or human-in-the-loop validation.
Integration of model outputs with Power BI, Power Apps, APIs, or operational applications.
Experience briefing technical results to operational users and senior leaders.

Principal responsibilities

Lead selection and refinement of the three baseline AI/ML use cases.
Define the mission question, data requirement, technical baseline, performance metric, and acceptance criteria for each model.
Perform data exploration, feature engineering, model development, comparative evaluation, and error analysis.
Work with the GCSS-Army SME to validate business rules and interpret model results.
Work with the Azure Data/MLOps Engineer to package, deploy, monitor, version, and sustain models.
Develop GenAI, RAG, forecasting, anomaly detection, or recommendation capabilities as selected.
Establish human-review procedures where model outputs affect operational decisions.
Prepare model cards, evaluation results, known limitations, release documentation, and retraining criteria.
Support integration of model findings into dashboards and Power Apps.
Participate in demonstrations and CASCOM production-readiness reviews.

Location and Work Expectations:

Ability to work remotely during normal Government working hours and participate in daily status, requirements, development, and technical-review sessions.
Ability to travel to Fort Lee, Virginia, at least three times annually and report onsite more frequently if directed.

Skills Required

Active Secret clearance
Hands-on production AI/ML development
Strong Python capability
Strong SQL capability
Experience taking at least one model from requirements through production or operational deployment
Experience with Azure-based AI/ML services or a comparable cloud environment
Ability to explain model evaluation, deployment, monitoring, and retraining
Bachelor's degree in computer science, data science, statistics, mathematics, operations research, engineering, or related discipline (or equivalent specialized experience)
Seven or more years in data science, machine learning, advanced analytics, or applied AI
Four or more years developing machine-learning solutions
Experience delivering at least three substantive models or AI capabilities, with at least one in production
Proficiency with pandas, NumPy, scikit-learn, and one major ML or deep-learning framework
Experience with two or more of: forecasting, anomaly detection, classification, recommendation engines, optimization, document extraction, NLP/RAG/GenAI
Experience defining measurable model-performance criteria
Experience with feature engineering, training/validation/test data, error analysis, explainability, and model documentation
Ability to travel to Fort Lee, Virginia at least three times annually and report onsite more frequently if directed
Experience with Azure Machine Learning, Azure OpenAI, Azure AI Search, Microsoft Copilot, or comparable Azure AI services
Experience in defense logistics, maintenance, readiness, fleet, supply chain, acquisition, property, or financial analytics
Experience with GCSS-Army, SAP ECC, ERP, or maintenance-system data
Experience with classified or Government-cloud deployment
Experience with model monitoring, drift detection, bias testing, red teaming, or human-in-the-loop validation
Experience integrating model outputs with Power BI, Power Apps, APIs, or operational applications
Experience briefing technical results to operational users and senior leaders