Senior Staff Engineer, Data Science

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Staff Engineer, Data Science in India.

In this senior technical leadership role, you will design and deliver end-to-end data science solutions that power intelligent, scalable digital products across global markets. You will work on complex real-world problems involving machine learning, generative AI, and advanced analytics, transforming large-scale data into actionable insights and production-ready systems. This role requires strong architectural thinking to define complete ML system designs, from data ingestion and model training to deployment and monitoring. You will also contribute to shaping AI-driven solutions using modern approaches such as LLMs, RAG systems, and prompt engineering. Operating in a highly collaborative and fast-evolving engineering environment, you will mentor teams, influence technical direction, and ensure high standards of engineering excellence. This is a high-impact role suited for someone who thrives at the intersection of data science, software engineering, and AI innovation.

• Design and define end-to-end data science and machine learning system architectures, including data pipelines, model training, inference, and deployment frameworks.
• Develop and optimize machine learning models across classification, regression, forecasting, clustering, recommendation systems, and NLP use cases.
• Apply statistical methods and advanced analytics to solve complex business and product challenges.
• Build and deploy scalable ML solutions using Python, ML libraries (such as scikit-learn), and cloud platforms (AWS, Azure, or GCP).
• Contribute to generative AI solutions including prompt engineering, retrieval-augmented generation (RAG), and LLM-based applications.
• Ensure high-quality code delivery, review peer work, and maintain strong engineering standards across projects.
• Lead technical design discussions, evaluate solution approaches, and define frameworks, tools, and methodologies.
• Support deployment activities including UAT, production rollouts, troubleshooting, and post-release monitoring.
• Identify technical risks early and propose effective mitigation strategies.
• Mentor and guide team members, fostering a culture of knowledge sharing, collaboration, and continuous improvement.

Requirements:

• 7+ years of experience in data science, machine learning, or applied AI engineering roles.
• Strong foundation in data science fundamentals, statistics, probability, and data analysis.
• Hands-on experience with Python or R for data science and machine learning development.
• Proven expertise in ML techniques including forecasting, classification, regression, NLP, and recommendation systems.
• Strong experience in model deployment, packaging, and production-grade ML systems.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Solid understanding of data visualization, SQL, and data analysis techniques.
• Exposure to generative AI, including prompt engineering and RAG-based architectures.
• Strong system design skills with the ability to define scalable ML architectures.
• Excellent problem-solving, debugging, and troubleshooting skills across complex environments.
• Strong communication skills with the ability to articulate technical solutions clearly.
• Experience mentoring engineers and contributing to team capability development.
• Bachelor’s or master’s degree in Computer Science, Information Technology, or a related field.

Benefits:

• Opportunity to work on cutting-edge AI, machine learning, and generative AI solutions at global scale.
• Exposure to diverse, complex, and high-impact data science challenges across industries.
• Flexible and collaborative work culture within a global engineering organization.
• Strong focus on continuous learning, upskilling, and career development.
• Opportunity to mentor and grow within high-performing engineering teams.
• Dynamic, non-hierarchical environment encouraging innovation and ownership.
• Work with modern cloud and AI technologies across AWS, Azure, and GCP ecosystems.