Data Science & AI/ML Lead (EDA Experience)
Level: SM
Role Overview
A hands-on Data Science and AI/ML Lead responsible for owning the end-to-end model training lifecycle, starting from EDA and feature engineering through training, evaluation, and deployment readiness. The role focuses on building reproducible, production-grade ML pipelines and ensuring data and models are optimized for performance, scalability, and reliability.
Key Responsibilities
1. Exploratory Data Analysis & Model Development
· Translate business problems and Use cases into model-ready ML formulations.
· Perform deep EDA and data profiling to understand patterns, data quality, and feature relevance
· Define feature engineering strategy aligned to model performance objectives
· Ensure reproducibility through dataset versioning and experiment tracking
· Define pipeline strategy for continuous retraining and validation.
· Train and optimize models for classification, regression, clustering, and anomaly detection, LLM/SLM Pretraining and Finetuning, etc.
· Perform hyperparameter tuning and model selection for optimal performance
· Drive trade-offs across accuracy, latency, cost, and interpretability
3. Scoring, Evaluation & Benchmarking
· Define evaluation and scoring frameworks for Datasets and certify for AI Readiness (Model Training)
· Conduct error analysis and benchmarking across datasets and model versions
· Establish acceptance thresholds and quality gates for production readiness.
4. Scalable ML & MLOps Enablement
· Enable ML lifecycle practices including model versioning, tracking, and monitoring
· Work with cloud platforms (Azure/AWS/GCP) for scalable training and deployment
· Collaborate with engineering teams to ensure production-grade integration
· Optimize platform performance, reliability, and scalability.
Required Capabilities / Skills / Experience
· 12+ years in Data Science / Machine Learning with strong hands-on experience
· Strong expertise in Python and ML/DL frameworks (scikit-learn, PyTorch, TensorFlow)
· Deep experience in EDA, feature engineering, and model training pipelines
· Experience building production-grade ML pipelines and evaluation frameworks
· Exposure to cloud ML platforms (Azure/Vertex/SageMaker)
· Experience with large-scale data processing and distributed training
· Hands-on experience with classical ML algorithms (Decision Trees, Random Forest, XGBoost, Gradient Boosting etc.)
· Exposure to LLM/SLM training or fine-tuning techniques (PEFT, LoRA, fine-tuning workflows)
· Exposure to LLM / GenAI workflows as integration points
· Familiarity with data quality, labelling, and dataset curation at scale
· Strong problem-solving and system thinking skills.
About us
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, building the bridge 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, realize tangible returns and keep global enterprises ahead in a fast-changing world. See how at www.cognizant.com 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.
Language requirements vary depending on roles, but we ask that all candidates have basic English proficiency for company-wide communications purposes. For roles based in Quebec, professional English proficiency is required, as you’ll deliver services to and collaborate with stakeholders outside the province who may not speak French.
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, provincial or local laws.
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.
