Data Scientist

We are looking for passionate and outcome-driven Data Scientists who enjoy solving complex business problems using Artificial Intelligence and Machine Learning. In this role, you will work on designing, developing, and deploying scalable AI/ML solutions that drive real business impact.

As a Senior Data Scientist, you will collaborate with engineering, product, and business teams to build production-ready machine learning models across use cases such as NLP, intelligent automation, anomaly detection, predictive analytics, and decision support systems.

Key Responsibilities

• Design, develop, and deploy end-to-end machine learning solutions.
  
• Build and optimize NLP and deep learning models for production use.
  
• Analyse large and complex structured and unstructured datasets to generate actionable insights.
  
• Translate business problems into scalable AI/ML solutions.
  
• Partner with engineering teams to deploy, monitor, and continuously improve ML models.
  
• Conduct model experimentation, hyper parameter tuning, and performance evaluation.
  
• Implement model monitoring, retraining strategies, and performance optimization.
  
• Present technical findings and business insights to both technical and non-technical stakeholders.
  
• Mentor junior data scientists and contribute to best practices across the team.
  
  

Requirements

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.
  
• 3–9 years of hands-on experience in Data Science, Machine Learning, Applied AI, or Advanced Analytics.
  
• Strong understanding of Machine Learning algorithms, Statistics, Probability, and Optimization techniques.
  
• Solid experience with Python (preferred) or Scala.
  
• Experience with model evaluation techniques, experimentation, and A/B testing.
  
• Strong problem-solving and analytical skills.
  
• Excellent communication and stakeholder management abilities.
  
  

Preferred Skills

• Experience with Natural Language Processing (NLP), Large Language Models (LLMs), or Generative AI.
  
• Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.
  
• Knowledge of text mining, embeddings, vector databases, and transformer-based models.
  
• Experience deploying ML models in cloud or production environments.
  
• Familiarity with MLOps, model monitoring, versioning, and CI/CD pipelines.
  
• Understanding of model explainability and interpretability techniques.