Tellius3mo ago

AI Solutions Consultant

India·Bangaloremid

Data ScienceSalesData ScientistSales EngineerDataData & AI

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Quick Summary

Overview

Tellius enables organizations to get faster insights and act upon cloud-scale enterprise data using AI-powered automation. Any user can ask any question across billions of records via a ChatGPT-like interface, understand “why” metrics change via AI insights that surface hidden key drivers and…

Key Responsibilities

Own end-to-end implementation of Tellius at named enterprise customers, from kickoff through production rollout Lead customer-facing workshops to extract use cases, requirements, and success metrics Build the semantic layer (Business Views) and…

Requirements Summary

Curious, analytical, and business-minded Comfortable working in ambiguity and bringing structure to it Excited about AI-native analytics and agentic systems A strong communicator who can turn insights into action Comfortable being the most senior…

Technical Tools

bigquerychatgptlookerpower-bisnowflakesqltableaumachine-learningsaas

Tellius enables organizations to get faster insights and act upon cloud-scale enterprise data using AI-powered automation. Any user can ask any question across billions of records via a ChatGPT-like interface, understand “why” metrics change via AI insights that surface hidden key drivers and trends, and leverage agentic flows to perform complex multipart analysis easily — in a self-service manner. Unlike traditional BI tools, Tellius excels at ad hoc analysis, deep dives, and business-friendly advanced analytics.

Responsibilities

~1 min read

→Own end-to-end implementation of Tellius at named enterprise customers, from kickoff through production rollout
→Lead customer-facing workshops to extract use cases, requirements, and success metrics
→Build the semantic layer (Business Views) and source data models - joins, aggregations, business rules - against customer data in Snowflake, Databricks, Redshift, or BigQuery
→Design and develop agentic workflows wrapping Tellius’s Ask, Investigate, and Automate capabilities around customer-specific business questions
→Configure Kaiya, our conversational AI interface, against customer semantic models and validate against real business questions
→Translate ambiguous business problems in brand, commercial, market access, and medical affairs into reproducible analytics workflows
→Partner with US-based CSMs, SEs, and AEs on account strategy, QBRs, and expansion conversations
→Present recommendations and demos confidently to business and technical stakeholders, including senior customer leadership
→Document patterns and contribute to a growing library of reusable implementation assets

3–7 years in client-facing analytics, consulting, or solutions roles - ideally from Axtria, ZS, Indegene, Beghou, ProcDNA, IQVIA Commercial Analytics, Cognizant Life Sciences, Fractal, Tiger Analytics, or equivalent
Strong hands-on SQL - window functions, complex joins, aggregations; able to debug and optimize a 200-line query without help
Hands-on experience with cloud data platforms - Snowflake, Databricks, Redshift, or BigQuery
Working familiarity with LLMs and agentic AI - prompt engineering, RAG pipelines, multi-step reasoning, tool usage, memory, and orchestration; you’ve designed around hallucination and built beyond basic ChatGPT usage
Experience with at least one major BI/analytics platform - Tableau, Power BI, ThoughtSpot, Looker, Qlik, or Sigma (you understand what Tellius replaces)
Practical understanding of machine learning - you don’t need to train models, but you can explain feature importance, classification vs. regression, and overfitting to a non-technical customer
Excellent written and spoken English - you will be on US customer calls every day
Willing to work US Eastern overlap hours as a core part of the role, not an occasional ask

Nice to Have

~1 min read

Pharma/life sciences project experience - IQVIA (TRx, NRx, NBRx, sub-national), Symphony Health, APLD, ARDs (Axtria), 867 data, sales operations data, claims
Implementation experience at large enterprises (vs. building internal dashboards at one company)
Multi-stakeholder navigation - you’ve handled the situation where IT says no and the business says yes, and brought both to alignment
Familiarity with pharma commercial use cases - brand analytics, commercial execution, market access, or medical affairs
Prior experience at an analytics or AI SaaS product company