About the Role

We are looking for a business-first analyst who thinks in outcomes, not dashboards. You will sit at the intersection of business strategy, analytics, and applied AI, translating stakeholder problems into data-driven answers, and using AI agents and automation to make analytics faster, cheaper, and more repeatable. This is not a pure data role and not a pure AI engineering role.

It is for someone who understands how the business makes money, can hold a room of senior stakeholders, and knows how to put modern AI tooling to work on real day-to-day analytics problems.

What You Will Do:

Business analytics & stakeholder management

- Own the analytics agenda for one or more business units and understand their P&L;, KPIs, operating rhythm, and decision cycles.
- Partner with functional and leadership stakeholders to frame problems, define success metrics, and drive decisions with evidence.
- Present findings and recommendations to senior leadership; build alignment and challenge assumptions with data where needed.
- Take end-to-end accountability for analytics deliverables: scope, quality, timelines, and business impact.

Reporting & data

- Design, build, and maintain Power BI dashboards and self-serve reporting that leadership actually uses.
- Write and optimize SQL across large datasets; define metric logic and ensure a single source of truth.
- Work with data engineering on data models, pipelines, and data-quality issues that block good analysis.

Applied & agentic AI

- Identify high-value, repetitive analytics workflows (report generation, variance commentary, data QA, ad-hoc query handling,



root-cause analysis) and automate them using LLMs and AI agents.
- Design and deploy agentic workflows (multi-step agents that pull data, run analysis, generate insights, and route outputs to stakeholders) with appropriate guardrails and human review.
- Evaluate and integrate AI tools (LLM APIs, agent frameworks, Copilot-style assistants, RAG over business documentation) into the analytics stack.
- Act as the internal evangelist for AI-augmented analytics by coaching analysts and business users on effective, responsible use.

What We Are Looking For Must-have

- 2+ years in business analytics, business intelligence, or a similar role with direct exposure to business decision-making.
- Strong commercial acumen. You can explain how a business works and where the levers are.
- Proven ability to influence and convince senior stakeholders; comfortable with pushback and ambiguity.
- Demonstrated ownership: you have shipped things end to end and are accountable for outcomes, not just outputs.
- Advanced Power BI (data modelling, DAX, performance tuning, row-level security, deployment).
- Advanced SQL (complex joins, window functions, CTEs, query optimisation).




- Hands-on experience with applied AI in a business context, including prompt engineering, LLM APIs, and building or deploying AI agents / agentic workflows (e.g. LangChain/LangGraph, CrewAI, AutoGen, Copilot Studio, Claude/OpenAI agent SDKs, or equivalent).
- Practical understanding of where AI agents work well, where they fail, and how to design for reliability, cost, and governance.

Valuable to have

- Python for analysis and automation (pandas, notebooks, APIs).
- Experience with RAG, vector databases, or fine-tuning for internal knowledge use cases.
- Exposure to Power BI + AI integrations (Copilot in Power BI, Fabric, Azure OpenAI).
- Experience in fintech, lending, or BFSI is a plus.
- Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks, Azure Synapse).

Who You Are

- Business-outcome obsessed. You start from the decision, not the data.
- A clear communicator who can simplify complexity for non-technical leaders.
- Curious and pragmatic about AI. Excited by what agents can do, sceptical enough to test before trusting.
- Comfortable owning a problem with no playbook and being the person leadership calls when something needs to get done.

What Success Looks Like in 12 Months

- Leadership relies on your dashboards and analysis for key operating decisions.
- At least 3 to 5 recurring analytics workflows are running through AI agents with measurable time savings.
- Stakeholders see you as a trusted advisor, not a report builder.
- The analytics team's use of AI tooling has visibly matured because of you.

📌 Business Analyst (Gurugram)
🏢 Ambak
📍 Gurugram