Data Scientist

Job Summary

Cognizant Tech Solution is seeking a Senior AIML Scientist to design, build, and scale machine learning systems that power personalization, customer intelligence, and decision-making across the business. You will work at the intersection of classical ML, statistical modeling, and emerging Generative and Agentic AI capabilities, partnering with engineering, product, and business stakeholders to turn data into measurable impact.

Responsibilities

• Design, develop, and deploy production-grade propensity models, recommendation engines, and other predictive ML systems end-to-end.
• Lead applied research and rigorous statistical analysis to inform model design, experimentation, and business strategy.
• Build, train, and operationalize models on Google Cloud Platform (GCP) using services such as Vertex AI, BigQuery, ML, Dataflow, and Cloud Run.
• Prototype and integrate Generative AI and Agentic AI capabilities into existing ML workflows and customer-facing products.
• Partner with data engineering teams to design feature stores, training pipelines, and model monitoring frameworks.
• Translate ambiguous business problems into well-scoped ML solutions and communicate results clearly to technical and non-technical audiences.
• Mentor junior data scientists and contribute to best practices in modeling experimentation and MLOps.

Requirements

• PhD in Computer Science, Statistics, Machine Learning, Applied Mathematics, or a related quantitative discipline.
• 5+ years of hands-on industry experience building and deploying ML models in production.
• Deep expertise in propensity modeling, recommendation systems, and statistical analysis (causal inference, AB testing, experimental design).
• Proven experience developing and deploying ML models on Google Cloud Platform including services like Vertex AI and BigQuery.
• Solid working knowledge of Generative AI and Agentic AI, LLMs, RAG, prompt engineering, agent frameworks, and evaluation methods.
• Strong Python programming skills with proficiency in libraries such as scikit-learn, TensorFlow, or PyTorch, pandas, and NumPy.

Qualifications

Location: must be based in and authorized to work in the United States or Canada.

Skills

• Google Professional Machine Learning Engineer or equivalent industry certification in cloud-based machine learning and ML Ops.

Pay

N/A

Schedule

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Benefits

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