Data Scientist

We are seeking an experienced

Senior Data Scientist

to lead the development of advanced machine learning, AI, and analytics solutions for enterprise-scale business challenges. The role focuses on designing production-grade ML systems, driving research and innovation, building modern AI architectures such as feature stores, knowledge graphs, and GenAI applications, and collaborating across engineering teams to deliver scalable, data-driven solutions. The ideal candidate combines deep technical expertise with strong business acumen and leadership skills.

Key Responsibilities:

• Design, develop, deploy, and optimize advanced machine learning models for business-critical use cases.
• Build predictive analytics, recommendation systems, forecasting, anomaly detection, optimization, and causal inference models.
• Develop experimentation frameworks including A/B testing, uplift modeling, and multi-armed bandits.
• Research, prototype, and evaluate emerging AI technologies including deep learning, graph AI, LLMs, and optimization techniques.
• Design and implement enterprise feature stores with feature governance, versioning, lineage, and reusable feature engineering frameworks.
• Develop knowledge graph solutions for entity resolution, relationship discovery, semantic enrichment, fraud detection, and intelligent recommendations.
• Productionize ML models through scalable deployment pipelines, CI/CD automation, model monitoring, drift detection, retraining strategies, and governance.
• Collaborate with Data Engineering teams to build scalable data pipelines, improve data quality, and support modern lakehouse architectures.
• Build and evaluate GenAI solutions including RAG applications, LLM fine-tuning, vector search, agentic workflows, and hallucination mitigation strategies.
• Translate business problems into AI-driven solutions while mentoring junior team members and presenting technical recommendations to stakeholders.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• 6–10+ years of experience in Data Science, Machine Learning, or Artificial Intelligence.
• Proven experience designing, deploying, and maintaining production-scale machine learning systems.
• Strong expertise in statistics, machine learning, optimization techniques, and predictive modeling.
• Experience with large-scale enterprise datasets and modern data platforms.
• Hands-on experience with Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.
• Experience with MLOps, CI/CD, model monitoring, and cloud platforms (Azure, AWS, or GCP).
• Familiarity with feature stores, graph databases (e.g., Neo4j, Amazon Neptune), and knowledge graph technologies.
• Experience building or supporting GenAI/LLM solutions, including RAG, vector databases, and prompt engineering, is highly preferred.