Gen AI Business Analyst- Remote at Cognizant - Thailand

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Full Time

Start Date

Immediate

Expiry Date

17 Dec, 25

Salary

105000.0

Posted On

18 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Large Language Models, Natural Language Processing, AI Model Development, Data Privacy, Document Anonymization, Analytical Skills, Documentation Skills, Model Validation, Insurance Domain, Communication Skills, Collaboration Skills

Industry

IT Services and IT Consulting

Description

Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process outsourcing services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.). Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 1000, and the Fortune 500 and we are among the top performing and fastest growing companies in the world. This role is not open to candidates who require visa sponsorship. We are only considering candidates who do not need visa sponsorship. Position: Gen AI Business Analyst Experience: 7 to 11 years We are seeking a highly skilled and experienced Gen AI Business Analyst to join our team. The ideal candidate will have a strong background in Large Language Models (LLMs), Natural Language Processing (NLP), and AI model development. Experience in the Property & Casualty Insurance domain is a strong advantage. Key Responsibilities: Collaborate with the data science team to prepare source documents for AI model development. Ensure data privacy and compliance by anonymizing sensitive information in documents. Label and categorize documents to support supervised learning and model training. Extract and structure content from documents to create organized outputs for model input. Analyze outputs from LLMs and validate them against ground truth data. Conduct manual testing and validation to assess model accuracy and relevance to business and functional requirements. Provide insights and feedback to improve model performance and alignment with business goals. Required Skills: Proven experience working with LLMs, NLP, and AI models. Strong analytical and documentation skills. Familiarity with data privacy standards and document anonymization techniques. Ability to interpret and validate AI model outputs. Experience in insurance domain, especially Property & Casualty, is a plus. Excellent communication and collaboration skills. Technical Competencies: Applicants will be accepted till 9/30/2025 The annual salary for this position will be in the range of $100K-$105K depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans. Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements: Medical/Dental/Vision/Life Insurance Paid holidays plus Paid Time Off 401(k) plan and contributions Long-term/Short-term Disability Paid Parental Leave Employee Stock Purchase Plan Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law. Our strength is built on our ability to work together. Our diverse backgrounds offer different perspectives and new ways of thinking. It encourages lively discussions, creativity, productivity, and helps us build better solutions for our clients. We want someone who thrives in this setting and is inspired to craft meaningful solutions through true collaboration. If you are content with ambiguity, excited by change, and excel through autonomy, we’d love to hear from you! #LI-AV1#CB#Ind123

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Responsibilities

The Gen AI Business Analyst will collaborate with the data science team to prepare source documents for AI model development and ensure data privacy and compliance. They will also analyze outputs from LLMs and validate them against ground truth data.