About the RoleWe are looking for a Senior Data Scientist with strong expertise in building and deploying production-grade Machine Learning systems. The ideal candidate should have deep hands-on experience in Traditional Machine Learning, MLOps, statistical modeling, and feature engineering, along with a proven ability to deliver scalable solutions that drive measurable business impact in regulated domains.

Key Responsibilities

- Design, develop, and deploy end-to-end Machine Learning models using Python, Scikit-learn, XGBoost, and other advanced algorithms.
- Build robust data pipelines, feature stores, and production ML systems with a strong focus on performance, scalability, and reliability.
- Implement MLOps practices including experiment tracking (MLflow), model versioning, CI/CD pipelines, Docker, Kubernetes, model monitoring, and drift detection.
- Apply statistical modeling, causal inference, and experimentation techniques (A/B testing, uplift modeling) to solve complex business problems.
- Collaborate closely with business stakeholders to understand requirements and translate them into high-impact ML solutions.
- Ensure model governance, explainability (SHAP/LIME), and compliance in regulated environments.
- Mentor junior data scientists and contribute to building reusable frameworks and best practices.

Must-Have SkillsCategorySkillsPriorityTraditional MLXGBoost, Random Forest, Logistic Regression,



Feature Engineering, Handling Imbalanced Data, Model Evaluation, Cross-Validation, Hyperparameter TuningVery HighMLOps & DeploymentMLflow, Docker, Kubernetes, CI/CD, Model Monitoring, Data Drift Detection, Model GovernanceVery HighBusiness ImpactProven experience in delivering ML solutions with quantifiable business outcomesVery HighDomain ExperienceExperience in Banking, Insurance, or Pharmaceutical domainsHighProgrammingPython (Pandas, NumPy, Scikit-learn), SQL, PySparkHigh Good-to-Have Skills

- Experience with Generative AI and Agentic AI (RAG, LangChain, LangGraph, Vector Databases, Multi-Agent Systems)
- Hands-on experience with Causal Inference techniques (Propensity Score Matching, Difference-in-Differences)
- Strong knowledge of Explainable AI (SHAP, LIME)
- Experience with cloud ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI)
- Exposure to LLM fine-tuning (LoRA/QLoRA) or RAG evaluation frameworks (e.g., RAGAS)

Qualifications

- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
- 4+ years of hands-on experience in Data Science / Machine Learning, with a solid focus on production ML systems.
- Demonstrated ability to deliver business-impacting solutions with measurable ROI.
- Excellent problem-solving, analytical, and stakeholder communication skills.
-

📌 Data Scientist (Hyderabad)
🏢 KloudPortal ™ - Digital Engineering
📍 Hyderabad