Back to jobs

Senior AI Scientist – Business Intelligence

Bangalore, India

Pay
Salary not listed in the saved posting
Work setup
Unconfirmed
Employment
Unconfirmed
Apply at INTU

What you’ll work on

Full posting

As a Senior AI Scientist on BI, you will own AI/ML solutions end to end, from data curation through evaluation to production, applied directly to BI's reporting and financial-analysis surfaces.

  • Own delivery of end-to-end AI/ML solutions for BI surfaces, spanning modeling, evaluation, and production integration.

  • Partner with BI product, design, and engineering to shape what's worth building, grounded in usage and feedback signals from reporting surfaces.

From the employer’s posting
As a Senior AI Scientist on BI, you will own AI/ML solutions end to end, from data curation through evaluation to production, applied directly to BI's reporting and financial-analysis surfaces. You will work closely with BI's product, design, and engineering teams to bring machine learning and LLM-based approaches to problems like generating financial narratives, surfacing benchmarking insights on KPI Scorecards, and improving forecasting for Cash Flow and Budgets.
Responsibilities Own delivery of end-to-end AI/ML solutions for BI surfaces, spanning modeling, evaluation, and production integration. Select appropriate algorithms and approaches for financial and reporting problems, explain trade-offs, and identify common failure modes such as hallucination, bias, and drift.
Use AI agents as part of your own science workflow, including experiment orchestration, hyperparameter search, and simulation-based validation, and help set standards for which BI science tasks should be agent-driven. Partner with BI product, design, and engineering to shape what's worth building, grounded in usage and feedback signals from reporting surfaces. Apply responsible AI practices given that BI surfaces present financial figures directly to accountants and business owners, and mentor others on the same.

What you’ll bring

All qualifications

Core experience

  • 4+ years of applied ML or data science experience, ideally including work with financial, accounting, or structured tabular and time-series data.
  • Hands-on experience with LLMs and agentic AI systems, including prompting, fine-tuning, and evaluation of agent pipelines, alongside classical ML methods such as supervised and unsupervised learning, time-series forecasting, and anomaly detection.
  • Experience building end-to-end, reusable ML pipelines, from data acquisition and ETL through model deployment and monitoring.

Preferred experience

  • Proficient in Python and SQL, comfortable in a Linux environment, and experienced with large-scale distributed data systems such as Spark or Hive; familiarity with OLAP engines such as StarRocks is a plus.
Qualification wording
4+ years of applied ML or data science experience, ideally including work with financial, accounting, or structured tabular and time-series data.
Hands-on experience with LLMs and agentic AI systems, including prompting, fine-tuning, and evaluation of agent pipelines, alongside classical ML methods such as supervised and unsupervised learning, time-series forecasting, and anomaly detection.
Experience building end-to-end, reusable ML pipelines, from data acquisition and ETL through model deployment and monitoring.
Proficient in Python and SQL, comfortable in a Linux environment, and experienced with large-scale distributed data systems such as Spark or Hive; familiarity with OLAP engines such as StarRocks is a plus.
Education & alternatives
Qualifications - MS or PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or a related field, or equivalent practical experience. - 4+ years of applied ML or data science experience, ideally including work with financial, accounting, or structured tabular and time-series data.

Tools in this posting

  • Python
  • SQL
  • Hive
Source — Tool mentions in context
- Hands-on experience with LLMs and agentic AI systems, including prompting, fine-tuning, and evaluation of agent pipelines, alongside classical ML methods such as supervised and unsupervised learning, time-series forecasting, and anomaly detection. - Proficient in Python and SQL, comfortable in a Linux environment, and experienced with large-scale distributed data systems such as Spark or Hive; familiarity with OLAP engines such as StarRocks is a plus. - Experience building end-to-end, reusable ML pipelines, from data acquisition and ETL through model deployment and monitoring.

Job description

View original posting ↗

About the team

Intuit's Business Intelligence (BI) team builds the reporting and analytics experiences that millions of QuickBooks customers and accountants rely on every day, including Modern Reports, Management Reports, KPI Scorecards, Dashboards, and FP&A (Cash Flow, Budgets, Forecasting). The team is in the middle of extending these experiences with AI: conversational reporting through Omni, self-serve report building, and agentic development practices that let us build faster on a codebase spanning years of financial logic. We sit on one of Intuit's largest proprietary datasets, tens of billions of transaction rows across millions of small businesses, and we are scaling our platform (built on StarRocks) to support multi-entity, multi-currency customers at a new order of magnitude.

About the role


As a Senior AI Scientist on BI, you will own AI/ML solutions end to end, from data curation through evaluation to production, applied directly to BI's reporting and financial-analysis surfaces. You will work closely with BI's product, design, and engineering teams to bring machine learning and LLM-based approaches to problems like generating financial narratives, surfacing benchmarking insights on KPI Scorecards, and improving forecasting for Cash Flow and Budgets.


Responsibilities

Responsibilities


  • Own delivery of end-to-end AI/ML solutions for BI surfaces, spanning modeling, evaluation, and production integration.

  • Select appropriate algorithms and approaches for financial and reporting problems, explain trade-offs, and identify common failure modes such as hallucination, bias, and drift.

  • Curate task-specific datasets from Intuit's proprietary financial data, with data governance and privacy built in, and build evaluation benchmarks specific to BI use cases, such as the accuracy of generated financial commentary or KPI explanations.

  • Design AI-native features that balance latency, cost, and quality, including features embedded in agentic pipelines such as Omni conversational BI, and design evaluation approaches for non-deterministic agentic flows.

  • Track emerging research and apply novel ML methods, including causal inference, time-series forecasting, and NLP/LLMs, to BI problems such as anomaly detection in financial statements and multi-entity consolidation insights.

  • Use AI agents as part of your own science workflow, including experiment orchestration, hyperparameter search, and simulation-based validation, and help set standards for which BI science tasks should be agent-driven.

  • Partner with BI product, design, and engineering to shape what's worth building, grounded in usage and feedback signals from reporting surfaces.

  • Apply responsible AI practices given that BI surfaces present financial figures directly to accountants and business owners, and mentor others on the same.


Qualifications

Qualifications


  • MS or PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or a related field, or equivalent practical experience.

  • 4+ years of applied ML or data science experience, ideally including work with financial, accounting, or structured tabular and time-series data.

  • Hands-on experience with LLMs and agentic AI systems, including prompting, fine-tuning, and evaluation of agent pipelines, alongside classical ML methods such as supervised and unsupervised learning, time-series forecasting, and anomaly detection.

  • Proficient in Python and SQL, comfortable in a Linux environment, and experienced with large-scale distributed data systems such as Spark or Hive; familiarity with OLAP engines such as StarRocks is a plus.

  • Experience building end-to-end, reusable ML pipelines, from data acquisition and ETL through model deployment and monitoring.

  • Strong written and verbal communication skills, with the ability to explain technical and financial concepts to both technical and non-technical audiences.


Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. 

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on jobs.intuit.com. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Bangalore, India

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Oct 8, 2026
Recorded sightings
6

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.