Principal Specialist, Data Science & Analytics

Job Summary

Lead advanced data science and analytics initiatives within the Agentic AI department, translating business problems into scalable analytical solutions, predictive models, and decision intelligence products that improve productivity and operational performance.

Responsibilities

• Translate business priorities and operational challenges into clear data science problem statements, analytical approaches, and measurable outcomes.
• Design and deliver predictive, prescriptive, diagnostic, and exploratory analytics solutions supporting decision-making across business and operational domains.
• Develop machine learning models, statistical analyses, simulations, and optimization approaches using enterprise data assets.
• Support agentic AI use cases by defining data, model, workflow, evaluation, and decision-support requirements.
• Create reusable analytical assets, data science patterns, feature logic, and decision intelligence products that scale across business domains.
• Apply data science governance practices for model validation, performance monitoring, bias checks, versioning, and lifecycle management.
• Provide expert guidance to analysts, data scientists, engineers, and business teams on analytical methods, model design, and evaluation.
• Communicate insights, risks, limitations, and recommended actions to technical, operational, and executive stakeholders.

Requirements

• Bachelor’s Degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Engineering, Information Systems, or related discipline.
• Minimum 10 years of experience in data science, advanced analytics, machine learning, AI solution delivery, decision intelligence, or data product development.
• Strong experience translating business requirements into analytical solutions, developing models, evaluating performance, and deploying analytics into operational workflows.
• Advanced data science, machine learning, statistical modeling, optimization, simulation, and predictive analytics skills.
• Proficiency in Python, SQL, analytics platforms, notebooks, visualization tools, cloud data platforms, and MLOps practices.
• Knowledge of agentic AI concepts, generative AI, decision intelligence, and AI workflow design.
• Experience with data preparation, feature engineering, model validation, performance monitoring, drift detection, and lifecycle management.
• Understanding of responsible AI, explainability, transparency, bias awareness, human oversight, and governance controls.
• Ability to coach teams, review analytical work, manage ambiguity, and communicate with technical and executive audiences.
• Master’s Degree is preferred; experience with agentic AI, generative AI, MLOps, responsible AI, cloud data platforms, or enterprise analytics environments is preferred.

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