ML/AI Data Scientist
Role Summary
Build the matching, inference, and labeling models that resolve entities into golden records and bring Gemini-assisted intelligence into the ontology.
Key Responsibilities
• Own entity matching and bridging: design and build fuzzy and exact matching models to stitch duplicate entities into golden records.
• Build inference models to support data profiling — identifying patterns, relationships, and anomalies in profiled source data.
• Support the business-ontology effort with Gemini-assisted labeling models that classify records into business domains (Location, Asset, Service, Event, Work-ticket).
• Design and build labeling workflows combining weak supervision, LLM-assisted labeling, and human-in-the-loop review.
• Deploy and manage matching, inference, and labeling models on Vertex AI.
• Evaluate model performance (precision/recall, drift) and work with the Architect and Data Domain SME to validate outputs against ontology rules.
• Partner with the Backend/Agent Engineer to expose matching/labeling models as callable tools within the agent orchestration layer.
• Continuously retrain and tune models as new source data and golden-record feedback become available.
• Document model logic, training data lineage, and known limitations for each deployed model.
• Support QA in defining acceptance thresholds for model-driven outputs (matching accuracy, labeling precision).
Core Skills
• Entity resolution / matching: fuzzy and exact matching techniques for golden-record creation.
• Inference and pattern-detection modeling over profiled data.
• LLM-assisted labeling and classification (Gemini) with human-in-the-loop review design.
• Model deployment, evaluation, and drift monitoring on Vertex AI.
• Weak supervision and semi-supervised labeling workflow design.
Required Qualifications
• 5+ years in applied ML, including entity resolution, classification, or NLP-based matching.
• Strong Python; experience with PyTorch and/or scikit-learn.
• Hands-on experience deploying and evaluating models on Vertex AI.
• Experience with embeddings, LLMs, or NLP techniques for matching and classification.
• Experience designing labeling workflows (weak supervision, LLM-assisted, human-in-the-loop).
Preferred Qualifications
• Experience with knowledge graphs or ontology-aligned ML (feature use over graph data).
• MLOps experience (model versioning, monitoring, retraining pipelines).
• GCP ML Engineer certification.
Tools & Technologies
Vertex AI, Gemini APIs, Python, PyTorch, scikit-learn, BigQuery, Spanner Graph or equivalent graph platform (for feature/context retrieval)
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 language
Salary and Other Compensation:
Applications will be accepted until Month Day, Year. 11/30/2026
Salary and Other Compensation:
Applications will be accepted until Month Day, Year.
The annual salary for this position is between $110,000 - $125,000 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
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!
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关于高知特 (Cognizant)
高知特(Cognizant)(纳斯达克代码:CTSH)作为一家AI Builder和相关技术服务提供商,致力于通过打造全栈AI解决方案,帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长,将企业独特的业务场景融入科技系统,赋能组织释放人才潜能,推动切实成果,并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情,敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外,候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
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