Senior AI Business Analyst at IntouchCX – Hyderabad | Jobyssey

About the Job
We are seeking an elite AI Business Analyst to power our Prism Insights platform, an advanced analytics and AI solution that transforms customer interaction data into actionable business intelligence.
This role sits at the intersection of large-scale data analysis, prompt engineering & AI optimization, customer experience (CX) analytics, and executive-level storytelling.
The Senior AI Business Analyst will work with millions of customer interactions stored in Google BigQuery, designing intelligent systems that extract structured insights from unstructured conversations and translate them into measurable business impact. This is a builder + analyst + problem solver role—not traditional reporting.

As Senior AI Business Analyst, You Will…

Query, manipulate, and analyze large-scale datasets in Google BigQuery.
Work across:

Structured data (KPIs, QA scores, operational metrics).
Semi-structured data (JSON, metadata).
Unstructured data (customer conversations, transcripts).

Identify trends in:

Contact drivers.
Customer sentiment & resolution.
Operational friction (people, process, tools).

Build datasets and logic that power dashboards, reporting, and insight generation.
Design, test, and optimize prompts that:

Classify customer contact drivers.
Detect root causes and escalation points.
Measure resolution, sentiment, and CX outcomes.

Develop structured testing frameworks to:

Evaluate prompt accuracy and consistency.
Identify failure points, edge cases, and bias.

Continuously improve AI outputs through:

Calibration with human QA.
Iterative prompt refinement.
Performance tracking and version control.

Analyze large volumes of conversational data to extract:

Themes, trends, and emerging issues.
Customer pain points and breakdowns.
Opportunities for automation and self-service.

Apply NLP concepts and structured thinking to turn text into measurable insights.
Partner with operations teams to ensure insights reflect real-world customer behavior.
Build and maintain dashboards in Looker / Looker Studio (or similar BI tools).
Translate complex datasets into:

Executive summaries (WBRs, MBRs, QBRs).
Clear, actionable recommendations.

Connect insights directly to business outcomes:

Cost reduction.
Revenue opportunities.
Customer experience improvements.

Partner with Product, Operations, QA, and Data teams to align outputs with business needs.
Translate business questions into analytical frameworks and prompt logic.
Present insights and recommendations to both technical and non-technical stakeholders.
Act as a consultative partner, not just an analyst.
Build scalable data models for:

Contact taxonomy.
QA scoring frameworks.
CX metrics (Resolution, Sentiment, Effort)

Validate data accuracy across:

SQL outputs.
Prompt-generated results.
Reporting layers.

Maintain prompt documentation, version control, and governance standards.

As a Senior AI Business Analyst, You Need…

4–7+ years of experience in Data analytics, CX analytics, or AI analytics (Required).
Must have Advanced SQL skills with hands-on experience in Google BigQuery.
Experience working with large, complex datasets, semi-structured data (JSON), and unstructured text/conversational data.
Proven experience with prompt engineering, prompt testing, or AI output optimization
Strong analytical thinking; ability to move from raw data → insight → recommendation.
Must have experience building dashboards in Looker, Looker Studio, or similar tools.
Must have excellent communication skills with the ability to present insights clearly to stakeholders.
Experience analyzing customer conversations (contact center, CX, retail, or support environments).
Experience with:

NLP processing in Python
Text classification and evaluation

Experience using Python for:

Data validation.
Text processing.
Analytical workflows.

Ability to identify root causes (not just report metrics).
Ability to connect insights to business impact.
Experience working in fast-paced, ambiguous environments.
Experience with BI tools beyond Looker (Tableau, Power BI).
Exposure to machine learning or cloud AI tools (Vertex AI, AutoML).
Familiarity with QA frameworks or scorecard-based evaluations.
Experience in consulting, strategy, or client-facing analytics roles.
Close attention to detail and curiosity (cares about why outputs succeed or fail).
Strong problem-solving mindset with structured thinking.
Ability to balance technical depth with business context.
Proactive, organized, and able to manage multiple priorities.
Comfortable working independently while collaborating across teams.

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