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Client-Facing Analytics Consultant Job Opening In India, India – Now Hiring Fig Labs


Job description

Fig Labs is building the Fig Analytics Agent—an AI agentic analyst that monitors business data 24/7, explains what changed and why, and recommends next-best actions.

We help organizations move from static dashboards to agentic analytics — systems that think, learn, and act.


We’re hiring a Forward Deployed Data Analyst to work directly with customer data, define metrics trees across domains, and implement them on Snowflake, Databricks, and BigQuery.

You’ll also codify agentic analytics best practices (prompts, patterns, and QA) so our agent delivers deep, trustworthy insights.


What you’ll do

Design domain-specific metric trees that map business outcomes to drivers and granular KPIs for industries such as:

  • Sales & Revenue Operations (forecast, pipeline, attainment)
  • Marketing Analytics (funnel efficiency, attribution, engagement)
  • Retail Analytics (product availability, store execution, promotions)
  • Supply Chain Analytics (inventory turns, order fill rate, forecast bias)


Own end-to-end analytics builds for customers: from source profiling → modeling → metric definitions → validation → visualization → AI-agent prompts.


Implement metrics on modern cloud data platforms (Snowflake, Databricks, BigQuery) using SQL (and dbt or equivalent) with tested, reusable patterns.


Author agentic analytics prompts for the Fig Analytics Agent:

  • Few-shot exemplars, tool-use patterns, system/task prompts, safety/guardrails, evaluation criteria, and correction loops.


Create visualization playbooks (chart choices, small-multiples, uncertainty bands, baseline/target overlays) to communicate insights clearly.


Partner with stakeholders (RevOps, Marketing Ops, Merch/Ops, Supply Chain, Finance) to translate questions into analyzable hypotheses and decision-ready outputs.


Harden quality: write QA queries, metric unit tests, anomaly checks, and reconciliation steps (source vs.

modeled vs.

dashboard).


You’ll be great at this if you have

Expert SQL (window functions, CTEs, semi-structured data, performance tuning) and strong experience on Snowflake, BigQuery and/or Databricks.


Experience with RevOps, marketing analytics, retail analytics, or supply-chain analytics (consulting or forward-deployed roles a plus)


Hands-on with data modeling (star schemas, facts/dimensions, SCDs), semantic layers, and dbt (or similar) best practices.


Proven visualization sense (knowing when to use bars/lines, cohort heatmaps, waterfalls, funnel and Sankey for flow, control charts for stability, prediction intervals).


Comfortable building and validating metrics for:

  • Funnel analysis (MQL→SQL→Opportunity→Win)
  • Forecasting & reconciliation (weighted pipeline, quota/target alignment, MAPE/WAPE)
  • Cohort & retention, RFM/segmentation
  • Market Basket Analysis/affinity, ABC/XYZ classification
  • Attribution (rules-based, simple MMM/MTA concepts)
  • A/B testing basics and lift analysis
  • Anomaly detection & outlier triage


Familiarity with agentic/LLM workflows (prompt design, few-shot patterns, retrieval/context packaging, evaluation/guardrails) or strong motivation to learn fast.


Excellent stakeholder communication—turn ambiguous questions into crisp hypotheses, datasets, and decisions.


What success looks like (90 days)

30 days: Current customer schema profiled;
baseline metrics tree drafted for one domain (e.G., Sales) and validated with stakeholders.


60 days: Metrics implemented on a target platform (Snowflake/Databricks/BigQuery) with QA checks;
first agentic prompts producing reliable, cite-able analyses.


90 days: Reusable agentic analytics playbook (prompts + SQL patterns + tests + viz guide) shipped;
two domains live (e.G.,Sales + Marketing) with measurable decision impact.


Why Join
  • Be part of a team shaping the future of autonomous analytics agents.
  • Work directly with the founder team on real customer datasets and live demos.
  • Ship high-impact analytical content seen by enterprise audiences.
  • 100% remote and flexible — output and curiosity matter more than location.

Required Skill Profession

Business Operations Specialists


  • Job Details

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Are You Looking for Client Facing Analytics Consultant Job?

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Fig Labs adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying India laws and regulations

What Is the Average Salary Range for Client Facing Analytics Consultant Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in India. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

What Are the Key Qualifications for Client Facing Analytics Consultant?

Key qualifications for Client Facing Analytics Consultant typically include Business Operations Specialists and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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To improve your chances of getting hired for Client Facing Analytics Consultant, consider enhancing your skills. Check your CV/Résumé Score with our free Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.

Interview Tips for Client Facing Analytics Consultant Job Success

Fig Labs interview tips for Client Facing Analytics Consultant

Here are some tips to help you prepare for and ace your Client Facing Analytics Consultant job interview:

Before the Interview:

Research: Learn about the Fig Labs's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

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Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Client Facing Analytics Consultant interview at Fig Labs, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Fig Labs's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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