Machine Learning Engineer â Finance Analytics & Insights
Machine Learning Engineer â Finance Analytics & Insights
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Job Description
About the Team
The Finance Analytics & Insights (FA&I) team is transforming how Finance operates by embedding AI/ML into the core of our decision-making processes. We are building intelligent scalable data products that power use cases across forecasting anomaly detection case summarization and agentic automation. Our global team includes data product managers analysts and engineers who are passionate about delivering measurable business value.
Role Overview
We are seeking a highly motivated and analytically strong ML Engineer to join our India-based team. This role will support the development and scaling of AI/ML-powered data products that drive strategic insights across Finance. As an IC3-level individual contributor you will work closely with the Data Product Manager and Insights Analyst to build AI/ML solutions that deliver measurable business value.
Key Responsibilities
- Design build and deploy machine learning models that support use cases such as:
- Forecasting
- Anomaly detection
- Case summarization
- Agentic AI assistants
- Partner with the Insights Analyst to perform feature engineering exploratory data analysis and hypothesis testing
- Build and iterate on proof-of-concepts (POCs) to validate model design and demonstrate business value
- Collaborate with the Data Product Manager to align model development with product strategy and business outcomes
- Own and manage the Databricks instance for the FA&I teampartnering with the DT Data & Analytics team to define a roadmap of capabilities test and validate new features and ensure the platform supports scalable ML development and deployment
- Ensure models are production-ready scalable and maintainableworking closely with DT and D&A teams to integrate into enterprise platforms
- Monitor model performance implement feedback loops and retrain models as needed
- Contribute to agile product development processes including sprint planning backlog grooming and user story creation
Qualifications :
Required Skills & Experience
- 35 years of experience in machine learning engineering data science or applied AI roles
- Strong proficiency in Python and ML libraries (e.g. scikit-learn XGBoost TensorFlow PyTorch)
- Solid understanding of feature engineering model evaluation and MLOps practices
- Experience working with large datasets using SQL and Snowflake
- Familiarity with Databricks for model development and orchestration
- Experience with CI/CD pipelines version control (Git) and ML workflow tools
- Ability to translate business problems into ML solutions and communicate technical concepts to non-technical stakeholders
- Experience working in agile teams and collaborating with product managers analysts and engineers
Preferred Qualifications
- Experience working in or supporting Finance or Accounting teams
- Prior experience deploying models in production environments and integrating with enterprise systems
- Familiarity with GenAI prompt engineering or LLM-based applications is a plus
- Experience with MLflow Azure ML or similar platforms
- Comfort with async collaboration tools and practices including Teams recorded video demos and documentation-first communication
- Experience working in a global cross-functional environment with stakeholders across time zones
Key Behaviors & Mindsets
- Builders Mentality: You love turning ideas into working models and iterating quickly to improve them.
- Collaborative Engineer: You work closely with analysts and product managers to co-create solutions that solve real business problems.
- Customer-Centric: You care deeply about the end user and build models that are interpretable actionable and aligned with business needs.
- Bias for Action: You move fast test often and focus on delivering valuenot just code.
- Global Mindset: You thrive in a distributed team and proactively align to US morning hours (PST overlap) to keep momentum across geographies.
- Async-First Communicator: Youre comfortable working in a hybrid async environmentleveraging Teams recorded demos and documentation to keep work moving forward.
- Growth-Oriented: Youre always learningwhether its a new algorithm tool or business domainand you help others grow too.
Additional Information :
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible remote or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race color creed religion sex sexual orientation national origin or nationality ancestry age disability gender identity or expression marital status veteran status or any other category protected by law. In addition all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process or are unable to use this online application and need an alternative method to apply please contact for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations including the U.S. Export Administration Regulations (EAR) ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. 2025 Fortune Media IP Limited. All rights reserved. Used under license.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
