Lead Data Scientist

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CAI is a global services firm with over 9,000 associates worldwide and a yearly revenue of $1.3 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.

Job Summary

Job Description

We are looking for a Lead Data Scientist to lead the design, development, deployment, and lifecycle management of machine learning models across production systems. This position will be full-time and remote.

What You’ll Do

Translate business problems into ML solutions that move metrics

• Partner with stakeholders and SMEs to understand the domain, convert real problems into analytical form, and select the right methodology (ML, statistics, optimization, simulation)

• Define success metrics, evaluation approaches, and validation plans (including baseline comparisons and monitoring strategy)

Build high-quality ML models (the “real data science” part)

• Design, develop, and iterate on models (forecasting, regression, classification, clustering, anomaly detection, etc.) with strong feature engineering and disciplined experimentation

• Deliver clear, decision-ready insights and communicate methods/results to technical and non-technical audiences

Engineer models into production (the “ML Engineer” part)

• Productionize prototypes into robust ML systems with appropriate error handling, versioning, reproducibility, and deployment patterns

• Build and maintain automated pipelines for training/validation/deployment, with CI/CD practices designed for ML workflows

• Use AWS (SageMaker) and Databricks to operationalize training and inference workflows, with a clean separation of data engineering, feature engineering, and model logic.

Own model lifecycle management (tracking, registry, governance)

• Track experiments and manage model artifacts with MLflow, operating a disciplined model promotion process (e.g., staging to production)

• Leverage a model registry as a centralized system for model lineage/versioning and lifecycle management.

Operate production ML (monitoring, alerts, and continuous improvement)

• Implement observability across model and data health: drift detection, performance regression, and actionable alerts with runbooks

• Support and enhance existing production models (new features, improvements, reliability hardening), driving continuous improvement post-deployment.

What You'll Need

Required:

• Demonstrated hands-on experience building ML models and deploying/operating them in production (end-to-end ownership)

• Strong Python skills; ability to write clean, testable, maintainable code (refactoring, modularity, code review discipline)

• Experience with distributed data/ML workloads in PySpark and strong SQL/data wrangling capability

• Practical experience with AWS, especially SageMaker, and experience delivering ML workloads on Databricks

• Experience with MLflow for experiment tracking and model lifecycle workflows

• Strong communication skills and the ability to collaborate across functions to embed analytics into business processes

Preferred:

• Experience implementing CI/CD for ML systems (tests, data/contract checks, packaging, automated deployments)

• Experience with model monitoring/drift tooling and defining retraining triggers tied to business SLAs

• Experience with modern ML frameworks (e.g., PyTorch/TensorFlow) and GenAI/LLM workflows

• Manufacturing/industrial analytics exposure (quality, supply chain, pricing, forecasting).

Physical Demands

• Ability to safely and successfully perform the essential job functions

• Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings, etc.

• Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor

Reasonable accommodation statement

If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to [email protected] or (888) 824 – 8111.