Sr Data Scientist

'

: - ( - )

Experience: 2+ yrs

Location: Hyderabad, Telangana, India, Bengaluru

As a Sr Data Scientist, you will spearhead advanced analytical initiatives that fuse Operations Research, Natural Language Processing, and Deep Learning to unlock actionable insights and drive decision-making across multiple domains. Your role will involve designing and implementing end-to-end machine learning pipelines, leveraging Python and SQL to extract, clean, and model complex datasets. You will collaborate closely with cross-functional teams, translating business challenges into data-driven solutions and ensuring the scalability and robustness of solutions in production environments. With a focus on probabilistic modeling and optimization, you will continually refine models, evaluate performance, and communicate findings to both technical and non-technical stakeholders.

Requirements

• Develop and deploy scalable operations research models for resource allocation and logistics optimization.
• Engineer end-to-end NLP pipelines for text mining, sentiment analysis, and unstructured data transformation.
• Design, train, and fine-tune deep learning architectures (CNN, RNN, Transformer) for vision and language tasks.
• Write efficient, maintainable Python code and complex SQL queries to support data extraction and analysis.
• Conduct rigorous statistical analysis and probabilistic modeling to quantify uncertainty and risk.
• Collaborate with data engineers to ensure data quality, pipeline reliability, and system performance.
• Perform benchmark studies and comparative evaluations of algorithms and models.
• Mentor junior data scientists and provide technical guidance on best practices.
• Stay current with emerging research, tools, and techniques in operations research and NLP.
• Communicate insights and recommendations through executive-level presentations and reports.
• 2+ years of industry experience as a senior data scientist or equivalent role.
• Deep expertise in operations research, including linear programming, stochastic optimization, and simulation.
• Proven track record in natural language processing, with experience in tokenization, embeddings, and transformer-based models.
• Hands-on mastery of deep learning frameworks such as TensorFlow or PyTorch.
• Strong programming proficiency in Python, along with advanced SQL querying skills.
• Solid foundation in probability theory and Bayesian statistics.
• Experience deploying models in production using Docker, Kubernetes, or similar container orchestration tools.
• Excellent problem-solving skills and the ability to translate complex data problems into clear, actionable solutions.
• Strong communication abilities to effectively share findings with stakeholders at all levels.
• A passion for continuous learning and staying abreast of the latest research and industry trends.