Sr Data Scientist, AI Innovation

Posted Yesterday
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Pune, Mahārāshtra, IND
In-Office
Senior level
Cloud • Fintech • HR Tech
The Role
Lead development and productionization of AI/ML solutions for finance: build data pipelines, develop and deploy forecasting, classification, anomaly detection, and agentic LLM solutions; monitor models for performance and bias; partner with finance stakeholders to deliver automation, insights, and measurable business value while establishing responsible AI and governance practices.
Summary Generated by Built In

Your work days are brighter here.

We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

About the Team

Finance Transformation Office (FTO) is redefining the finance function through innovative data science, machine learning, and agentic AI solutions. We build intelligent automation that showcases Workday’s AI capabilities, streamlines complex financial processes, and turns data into actionable insights.
We are building an Agentic Finance Ecosystem: a connected set of intelligent agents that make financial data continuously decision-ready, automate end-to-end workflows, and unlock strategic capacity across Finance. Guided by a Customer Zero mindset, we apply our solutions internally first—proving measurable business value, establishing best practices, and creating benchmarks that help customers transform their own finance organizations.
Join a team where finance expertise, data science, and AI engineering come together to shape the future of intelligent finance.

About the Role

  • Expertise in data science and machine learning, with experience applying predictive analytics and statistical techniques to complex business problems.

  • Experience building production-oriented AI or ML solutions, including data preparation, model development, evaluation, deployment, and monitoring.

  • Familiarity with generative AI, large language models, retrieval-augmented generation, AI agents, and workflow orchestration.

  • Strong programming skills and experience working with large-scale, diverse data sources.

  • Ability to communicate technical concepts and analytical insights clearly to business stakeholders and influence decisions through data.

  • A practical, outcome-oriented mindset with a focus on delivering automation, insight, and measurable business value.

About You

Basic Qualifications:

  • 8 - 10 years experience with design, develop, and program methods, processes, and systems to consolidate and analyze diverse structured and unstructured data sources.

  • Build and deploy machine learning models for forecasting, classification, anomaly detection, optimization, risk identification, and fraud prevention.

  • Develop agentic AI solutions that can reason over finance data, orchestrate workflows, automate repetitive processes, and surface proactive recommendations.

  • Create robust data pipelines and automated processes to cleanse, integrate, validate, and evaluate large datasets from multiple disparate sources.

  • Partner with Finance stakeholders, product teams, and service organizations to identify analytical questions, define success metrics, and run data-driven experiments.

  • Apply statistical analysis, predictive modeling, natural language processing, generative AI, and optimization techniques to solve complex finance problems.

  • Translate complex findings into clear, meaningful, and actionable insights for technical and non-technical stakeholders.

  • Evaluate model performance, monitor production solutions, identify sources of bias or drift, and continuously improve solution quality, reliability, and business impact.

  • Establish best practices for responsible AI, model governance, data quality, privacy, and secure use of financial information.

  • Prototype and scale AI capabilities that demonstrate Workday’s Customer Zero approach, creating proven solutions and reusable patterns for broader customer value.

  • Collaborate with engineers to productionize models, integrate AI solutions into existing workflows, and ensure systems are scalable, maintainable, and performant.

  • Stay current on advances in AI, ML, data science, and agentic systems, applying new techniques where they can deliver tangible value for Finance.


Our Approach to Flexible Work
 

With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.


At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email
[email protected].

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

At Workday, we value our candidates’ privacy and data security.  Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. 

  

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

  

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

Skills Required

  • 8-10 years designing, developing, and programming methods to consolidate and analyze diverse structured and unstructured data sources.
  • Build and deploy machine learning models for forecasting, classification, anomaly detection, optimization, risk identification, and fraud prevention.
  • Experience building production-oriented AI/ML solutions including data preparation, model development, evaluation, deployment, and monitoring.
  • Develop agentic AI solutions and AI agents that reason over finance data, orchestrate workflows, and automate processes.
  • Familiarity with generative AI, large language models, and retrieval-augmented generation.
  • Create robust data pipelines and automated processes to cleanse, integrate, validate, and evaluate large datasets from multiple disparate sources.
  • Apply statistical analysis, predictive modeling, natural language processing, generative AI, and optimization techniques to finance problems.
  • Partner with finance stakeholders and product teams to define analytical questions, success metrics, and run experiments.
  • Translate complex findings into clear, actionable insights for technical and non-technical stakeholders.
  • Evaluate model performance, monitor production solutions for bias and drift, and continuously improve solution quality and business impact.
  • Establish best practices for responsible AI, model governance, data quality, privacy, and secure handling of financial information.
  • Collaborate with engineers to productionize models and ensure scalable, maintainable, performant systems.

Workday Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Workday and has not been reviewed or approved by Workday.

  • Healthcare Strength Health coverage is positioned as broad and well-supported, with multiple medical carrier options, virtual care access, and some locations offering onsite clinic/pharmacy services. Mental health support is described as notably strong, including therapy sessions and confidential support availability for household members.
  • Parental & Family Support Family-related benefits are portrayed as extensive, including paid bonding and caregiver leave alongside fertility, adoption, and surrogacy reimbursement. Added support like parenting resources, milk-shipping/lactation assistance during travel, and backup child/elder care is explicitly outlined.
  • Strong & Reliable Incentives Equity participation and savings-oriented programs are presented as meaningful components of total rewards, including an ESPP discount with a lookback feature. Additional programs like a student-loan pathway to earn the 401(k) match are included as financial-support enhancements.

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The Company
HQ: Pleasanton, CA
14,894 Employees
Year Founded: 2005

What We Do

Workday is a leading provider of enterprise cloud applications for finance, HR, and planning. Founded in 2005, Workday delivers financial management, human capital management, and analytics applications designed for the world’s largest companies, educational institutions, and government agencies. Organizations ranging from medium-sized businesses to Fortune 50 enterprises have selected Workday.

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