Data Scientist( 8 Yrs Hyderabad)

Primary Title:

About The Opportunity

Role & Responsibilities

• Lead end-to-end ML projects: translate business problems into data/ML solutions, design experiments, and deliver production-ready models.
• Architect and build scalable data pipelines and feature engineering workflows using PySpark and SQL for large datasets.
• Develop, validate, and optimize supervised and unsupervised models (classifiers, regressors, and deep learning models) to meet accuracy and latency targets.
• Deploy and operationalize models using containerization and MLOps practices: Docker, MLflow, model versioning, CI/CD, and cloud hosting (AWS SageMaker or equivalent).
• Define model evaluation strategies, A/B testing protocols, monitoring/alerting for drift and performance, and ensure reproducibility and observability in production.
• Collaborate with product managers and engineers, provide technical leadership, and mentor junior data scientists and engineers to raise team delivery quality.
  

Skills & Qualifications

Must-Have

• 8+ years of professional experience in applied data science, machine learning, or analytics roles (senior/lead level).
• Proven hands-on experience in Python and SQL for data manipulation, modeling, and production workflows.
• Practical experience with machine learning libraries and frameworks: scikit-learn and TensorFlow (or PyTorch) for model development.
• Experience with big-data processing and engineering: PySpark, data pipeline design, and ETL best practices.
• Production deployment and MLOps experience: Docker, MLflow, model monitoring, and cloud deployment (AWS SageMaker or equivalent).
• Strong statistical foundations, experiment design (A/B testing), and model evaluation techniques for robust production models.
  

Preferred

• Familiarity with Kubernetes, CI/CD tooling, or infrastructure-as-code for scalable deployments.
• Experience with model explainability, feature store technologies, or real-time inference systems.
• Prior exposure to domain-specific ML (NLP, time-series forecasting, or recommender systems) for enterprise use cases.
  

Benefits & Culture Highlights

• On-site role in Hyderabad with opportunities to lead high-impact ML programs for enterprise clients.
• Collaborative, engineering-driven culture offering mentorship, technical growth, and exposure to end-to-end MLOps.
• Competitive compensation, performance bonuses, and career progression into lead/architect roles.