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!
#LI-AV1#CB#Ind123
Additional employment information
Compensation 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.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
Applicants must be currently authorized to work for any employer in the United States. The company is unable to provide employment-based immigration sponsorship for this position.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
