Senior Data Scientist

Role & responsibilities

• Design, develop, and deploy advanced machine learning, deep learning, and AI models to solve complex business problems.
• Analyze large, structured, and unstructured datasets to generate actionable insights and support data-driven decision-making.
• Build predictive models, recommendation systems, NLP, computer vision, or Generative AI solutions based on business requirements.
• Develop and optimize feature engineering, model training, validation, and deployment pipelines.
• Collaborate with data engineers, software engineers, product managers, and business stakeholders to deliver scalable AI solutions.
• Implement MLOps best practices for model deployment, monitoring, retraining, and lifecycle management.
• Evaluate model performance using statistical techniques and continuously improve model accuracy and reliability.
• Work with cloud platforms (AWS, Azure, or GCP) and big data technologies to build scalable data science solutions.
• Mentor junior data scientists and contribute to technical leadership, code reviews, and knowledge sharing.
• Stay updated with emerging AI, machine learning, and data science technologies and recommend innovative approaches.

Preferred candidate profile

• Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative field; Master's degree or Ph.D. is preferred.
• 5 to 10 years of experience in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics.
• Strong expertise in Python, SQL, machine learning algorithms, deep learning frameworks (TensorFlow, PyTorch), and statistical modeling.
• Hands‑on experience with NLP, Generative AI, Large Language Models (LLMs), predictive analytics, and model deployment.
• Experience with cloud platforms (AWS, Azure, or GCP), Databricks, Apache Spark, MLflow, Docker, and Kubernetes is preferred.
• Strong knowledge of MLOps, feature engineering, model evaluation, data visualization, and big data technologies.
• Relevant certifications such as AWS Machine Learning Specialty, Azure Data Scientist Associate, Google Professional Machine Learning Engineer, or Databricks certifications are preferred.
• Excellent analytical, problem‑solving, communication, leadership, and stakeholder management skills.
• Ability to lead data science initiatives, mentor team members, and deliver scalable AI solutions in Agile environments.