Analytics Manager, Gen-AI & Automation

About the Role

Key Responsibilities

• Maintain, analyze, and execute on analytics-based projects.
• Prototype, fine-tune, and productionize LLM solutions such as OpenAI, Azure OpenAI, and Claude to generate analyses, documentation, and stakeholder summaries.
• Automate data-quality checks and metadata enrichment.
• Perform natural-language querying over SQL/Power BI models.
• Curate high-quality prompt libraries and retrieval-augmented generation (RAG) pipelines for repeatable insights.
• Define new AI-ready datasets and metrics; build self-service dashboards exposing raw data and LLM-generated commentary.
• Serve as an analytics translator, turning business problems into AI solutions and demystifying LLM outputs for non-technical partners.
• Continuously measure impact, speed, cost-to-insight, and accuracy, and iterate to improve results.
• Own AI/analytics projects from discovery through deployment using agile project management practices.
• Capture stakeholder feedback to refine prompts, improve model performance, and prioritize automation initiatives.
• Collaborate with senior team members to develop end-user reporting and analytics.
• Build strong cross-functional relationships and communicate effectively with stakeholders.

Requirements

• 6+ years of professional experience.
• 3+ years of programming experience in Python or R.
• 2+ years of experience with Natural Language Processing (NLP) and Large Language Models (LLMs).
• 2+ years of experience building and maintaining scalable API solutions.
• Strong SQL skills, including experience with Snowflake, Power BI, or Tableau.
• Experience evaluating hallucination, bias, and safety in GPT, Gemini, Claude, or similar models.
• Ability to turn complex AI concepts into plain language and communicate effectively with stakeholders.
• Experience designing rapid A/B tests and establishing evaluation metrics.
• Willingness to learn new tools and expand knowledge continuously.
• Proven ability to influence stakeholders and guide teams through data-backed recommendations.

Nice to Have

• Experience with prompt-engineering best practices.
• Familiarity with tools such as Cortex, Windsurf, and other data assets.
• Experience with APIs, vector databases, and CI/CD pipelines.
• Knowledge of data visualization and dashboard integration.
• Experience with AI safety, hallucination mitigation, and bias evaluation.

Qualifications

• Educational background not explicitly specified, but extensive professional experience required.

Benefits & Perks

• Health and financial benefits.
• Commuter support, employee assistance programs, and tuition reimbursement.
• Employee resource groups and collaborative workspaces.
• Flexible work arrangements to support work-life balance.
• Company-sponsored events such as book clubs, external speakers, and hackathons.