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.
4–6 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.

Work arrangement
No