Data Analytics Manager
Apollo Solutions, Hartford, CT, United States
Manager Data Analytics and AI Engineering
Connecticut, US
Our client, a global manufacturing company, is hiring a Manager for Data Analytics and AI Engineering to help modernize its Internal Audit function. This role focuses on building ML pipelines, deploying models, and creating LLM-driven solutions that enhance evidence gathering and risk assessment.
Role Highlights
Build scalable analytics and ML pipelines on Databricks for key audit activities
Develop and deploy models for anomaly detection, risk scoring, and predictive analysis
Create secure retrieval augmented generation solutions for sensitive audit material
Build LLM applications and coordinated agent workflows that automate triage and summarization
Produce dashboards in Power BI or Tableau that turn model outputs into clear insights
Maintain data quality standards and implement governance controls, including validation, explainability, and drift monitoring
Experience and Skills
Bachelor's Degree in Data Analytics, Computer Science, Information Systems, or a related field
Five or more years of experience in data science, ML engineering, or applied analytics, including production model deployments
Strong Python skills with experience using pandas, numpy, and ML frameworks such as scikit learn, PyTorch, or TensorFlow
Familiarity with experiment and metadata tracking tools such as MLflow
Experience building LLM-based applications, including RAG pipelines, embeddings, vector search, and prompt engineering
Understanding of agent orchestration concepts for coordinating multiple models or tools
Strong SQL and data modeling capability with the ability to translate audit needs into analytic design
Experience with operationalizing models, including serving, monitoring, and drift detection
If you want to shape the future of audit technology within a global manufacturing business, please apply.
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Connecticut, US
Our client, a global manufacturing company, is hiring a Manager for Data Analytics and AI Engineering to help modernize its Internal Audit function. This role focuses on building ML pipelines, deploying models, and creating LLM-driven solutions that enhance evidence gathering and risk assessment.
Role Highlights
Build scalable analytics and ML pipelines on Databricks for key audit activities
Develop and deploy models for anomaly detection, risk scoring, and predictive analysis
Create secure retrieval augmented generation solutions for sensitive audit material
Build LLM applications and coordinated agent workflows that automate triage and summarization
Produce dashboards in Power BI or Tableau that turn model outputs into clear insights
Maintain data quality standards and implement governance controls, including validation, explainability, and drift monitoring
Experience and Skills
Bachelor's Degree in Data Analytics, Computer Science, Information Systems, or a related field
Five or more years of experience in data science, ML engineering, or applied analytics, including production model deployments
Strong Python skills with experience using pandas, numpy, and ML frameworks such as scikit learn, PyTorch, or TensorFlow
Familiarity with experiment and metadata tracking tools such as MLflow
Experience building LLM-based applications, including RAG pipelines, embeddings, vector search, and prompt engineering
Understanding of agent orchestration concepts for coordinating multiple models or tools
Strong SQL and data modeling capability with the ability to translate audit needs into analytic design
Experience with operationalizing models, including serving, monitoring, and drift detection
If you want to shape the future of audit technology within a global manufacturing business, please apply.
#J-18808-Ljbffr