Data Analyst

Accenture Federal Services•Washington, DC

1d•$100,200 - $203,400

About The Position

At Accenture Federal Services, our mission is to help the US federal government strengthen the nation, enhance public safety, and improve citizens' lives through technology and ingenuity. We are a technology company within global Accenture, recognized as a Glassdoor Top 100 Best Place to Work. We foster a collaborative and supportive community where employees are empowered to grow, learn, and thrive through hands-on experience, certifications, and industry training. Join us to drive positive, lasting change and advance government missions.

Requirements

US Citizen (Public Trust eligible)
Strong data analysis skills: SQL and Python.
Working understanding of AI/ML concepts: LLMs, prompt engineering, model evaluation metrics, NLP fundamentals.
Experience with BI/visualization tools: Databricks, Splunk, Tableau, PowerBI, or similar.
Knowledge of conversational AI, chatbot analytics, and customer experience metrics.
Ability to communicate complex technical findings clearly and translate insights into executive-ready recommendations.

Nice To Haves

Hands-on experience with GenAI chatbot analytics for high-volume user environments (1M+ monthly users).
Direct involvement in LLM performance monitoring, guardrail testing, or RAG evaluation.
Prior work optimizing AI operational workflows such as model deployment or incident response.
Experience designing A/B tests or conducting deep-dive analysis on conversational data.
Familiarity with operational monitoring tools such as Splunk or Dynatrace.

Responsibilities

Analyze chatbot performance metrics such as user satisfaction, deflection rates, response accuracy, latency, and token usage.
Monitor LLM model performance to detect quality issues, edge cases, and opportunities for prompt or response optimization.
Perform deep-dive analyses on user feedback, conversation patterns, and intent classification to improve the product.
Design and execute A/B tests to measure the impact of new features, prompt changes, and model configurations.
Manage and optimize end-to-end workflows for model deployment, monitoring, and incident response.
Build automated alerting systems for operational metrics, SLAs, and AI performance thresholds.
Coordinate cross-functional workflows across data science, engineering, product, and business teams.
Identify and resolve data quality issues, pipeline bottlenecks, and system inefficiencies through root cause analysis.
Create and maintain dashboards in SQL, Python, and BI tools (Databricks, Splunk, Dynatrace).
Develop executive-level reports on chatbot performance, user trends, ROI, and contact center impact.
Build data documentation, metadata standards, and analytics playbooks for stakeholder self-service.
Track and report KPIs such as user engagement, task completion, escalation patterns, and cost per interaction.
Translate business problems into data-driven solutions with measurable success criteria.
Conduct qualitative and quantitative research to uncover user needs and feature opportunities.
Write user stories with data-backed acceptance criteria, wireframes, and process flows.
Lead requirements sessions and synthesize inputs into actionable insights and prioritized roadmaps.
Monitor guardrail effectiveness, content safety, and compliance with Responsible AI policies.
Analyze multi-turn conversation flows for issues like topic drift and response inconsistency.
Evaluate RAG performance including citation accuracy and knowledge base coverage.
Track model cost drivers such as token consumption and resource usage to optimize efficiency.