Machine Learning Scientist+Agentic
Job Summary
Architect role in a global organization focused on designing scalable data solutions using BigQuery ML Python and BigQuery. The architect will define modern analytics architecture enable advanced machine learning capabilities on cloud data platforms and guide teams to deliver secure high performance solutions that drive business value and social impact within a hybrid work model.
Responsibilities
- Design end to end cloud data architectures that leverage BigQuery and BigQuery ML to deliver scalable analytics platforms that support complex business reporting and predictive modeling needs for diverse stakeholder groups.
- Develop robust machine learning solutions in BigQuery ML using Python based feature engineering and model evaluation practices that improve decision quality across critical business processes and external customer services.
- Optimize data warehouse structures and BigQuery query performance by defining partitioning strategies clustering approaches and cost control mechanisms that ensure efficient use of resources and rapid insight generation.
- Collaborate with product owners data scientists and engineering teams to translate analytical requirements into technical blueprints that integrate BigQuery data assets Python workflows and downstream consumption layers.
- Establish standards for data ingestion transformation and storage in BigQuery including reusable patterns for Python based pipelines to ensure reliability auditability and consistent data quality across projects.
- Create architecture documentation and solution diagrams that clearly describe data flows security controls and integration touchpoints enabling teams to implement BigQuery and Python solutions with confidence and alignment.
- Guide teams on best practices for experimenting with BigQuery ML models including model selection training validation and monitoring to ensure models remain accurate ethical and relevant to business objectives.
- Coordinate hybrid work collaboration by defining processes and tools that support effective communication code review and design validation for team members working both onsite and remotely in day shift.
- Ensure security and compliance requirements are embedded into all BigQuery and Python solutions by applying encryption access control policies and data governance principles that protect sensitive information and build stakeholder trust.
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.
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.
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