Practice - AIA - Artificial Intelligence and Analytics
About AI & Analytics: Artificial intelligence (AI) and the data it collects and analyzes will soon sit at the core of all intelligent, human-centric businesses. By decoding customer needs, preferences, and behaviors, our clients can understand exactly what services, products, and experiences their consumers need. Within AI & Analytics, we work to design the future—a future in which trial-and-error business decisions have been replaced by informed choices and data-supported strategies.
By applying AI and data science, we help leading companies to prototype, refine, validate, and scale their AI and analytics products and delivery model
s. Cognizant’s AIA practice takes insights that are buried in data and provides businesses a clear way to transform how they source, interpret and consume their information. Our clients need flexible data structures and a streamlined data architecture that quickly turns data resources into informative, meaningful intelligence.
Job Summary
We are seeking a Senior Data Scientist with strong expertise in Exploratory Data Analysis (EDA), Machine Learning, Generative AI, and Large Language Models (LLMs). This role will focus on designing, tuning, evaluating, optimizing, and deploying enterprise-scale AI/ML solutions while contributing to the broader AI architecture roadmap. The ideal candidate will combine strong statistical and machine learning foundations with hands-on experience in RAG, LLM tuning, AI agents, model evaluation, and production AI platforms.
In this role, you will:
· Perform advanced Exploratory Data Analysis (EDA) and statistical analysis to identify patterns, relationships, anomalies, and actionable business insights.
· Design, develop, evaluate, and deploy machine learning models for predictive analytics, classification, regression, forecasting, and other enterprise use cases.
· Build Generative AI and LLM-based solutions, including RAG applications, AI agents, enterprise search, and knowledge-driven AI systems.
· Fine-tune, profile, benchmark, and optimize LLMs for model quality, latency, accuracy, scalability, and cost efficiency.
· Design model evaluation frameworks covering performance, relevance, hallucination, safety, robustness, and business effectiveness.
· Contribute to end-to-end AI/ML architecture across cloud and on-premises environments, including model serving, data pipelines, and integration patterns.
· Develop and operationalize MLOps/LLMOps pipelines for experimentation, versioning, deployment, monitoring, and continuous model improvement.
· Evaluate AI/ML frameworks, foundation models, vector databases, and emerging technologies based on business and technical requirements.
· Collaborate with data engineers, AI engineers, architects, product teams, and business stakeholders to translate requirements into scalable AI solutions.
· Ensure AI solutions follow enterprise security, data governance, responsible AI, and production-readiness standards.
What you need to have to be considered
· 6+ years of experience in Data Science, Machine Learning, AI Engineering, or Advanced Analytics roles.
· Expert knowledge of Exploratory Data Analysis, statistical methods, feature engineering, machine learning algorithms, and model evaluation techniques.
· 3+ years of strong hands-on Machine Learning experience developing and deploying production-grade models.
· Hands-on experience with Generative AI and LLMs, including prompt engineering, RAG, embeddings, vector databases, model tuning, evaluation, and performance optimization.
· Strong proficiency in Python and ML/AI frameworks such as Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, or equivalent technologies.
· Experience with LLM fine-tuning approaches, model benchmarking, inference optimization, and responsible AI practices.
· Familiarity with AI agents, multi-agent systems, MLOps/LLMOps, model monitoring, and enterprise AI platform architecture.
· Experience with major cloud AI/ML platforms such as Azure, AWS, or GCP and production deployment practices.
· Strong analytical, problem-solving, communication, and stakeholder collaboration skills with the ability to translate technical results into business outcomes.
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Applications will be accepted until 30 Oct 2026.
Salary and Other Compensation:
The annual salary for this position is between $[133,000 - 156,500] 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
Acerca de Cognizant
Cognizant (Nasdaq: CTSH) es un creador de soluciones de IA y proveedor de servicios tecnológicos que conecta la inversión en IA con el valor empresarial mediante el desarrollo de soluciones de IA full‑stack para sus clientes. Su profundo conocimiento de la industria, junto con su experiencia en procesos e ingeniería, permite incorporar el contexto único de cada organización en sistemas tecnológicos que amplifican el potencial humano, generan resultados tangibles y mantienen a las empresas a la vanguardia en un entorno en constante cambio. Más información en cognizant.ai o @cognizant.
Información adicional sobre el empleo
La información sobre la compensación es exacta en la fecha de publicación de este anuncio. Cognizant se reserva el derecho de modificar esta información en cualquier momento, de conformidad con la legislación aplicable.
Es posible que se solicite a los solicitantes que asistan a entrevistas de forma presencial o mediante videoconferencia. Asimismo, durante cada entrevista, los candidatos podrán estar obligados a presentar un documento de identidad válido emitido por el estado o por el gobierno.
Cognizant es un empleador que ofrece igualdad de oportunidades. Su solicitud y candidatura no se evaluarán en función de la raza, el color, el sexo, la religión, el credo, la orientación sexual, la identidad de género, el origen nacional, la discapacidad, la información genética, el embarazo, la condición de veterano ni cualquier otra característica protegida por las leyes federales, estatales o locales.
