Lead Data Scientist

Position Summary

As a Lead Data Scientist, you will lead a team of data scientists, machine learning engineers, and big data specialists to design, develop, and deploy data-driven solutions. You will be responsible for identifying business opportunities, translating them into data strategies, and driving measurable outcomes. This role demands strong leadership, deep technical expertise, and a passion for continuous innovation.

Key Responsibilities

• Manage a team of data scientists, machine learning engineers, and big data specialists.
• Lead data mining, data collection, and cleansing procedures.
• Ensure high standards of data quality and integrity across all projects.
• Interpret complex data sets to identify patterns, trends, and actionable insights.
• Conceive, plan, and prioritize data science initiatives aligned with business goals.
• Develop and deploy scalable analytics systems and predictive models.
• Test and validate data-driven products for performance and reliability.
• Create compelling visualizations and comprehensive reports for stakeholders.
• Experiment with emerging models and machine learning techniques for innovation.

Qualifications & Experience

• 6-8 years of working experience in Image Processing using deep learning frameworks such as OpenCV, PyTorch, TensorFlow, Theano, and Caffe.
• Experience in Text Analytics using NLP tools and techniques on unstructured data.
• Proven track record in building, deploying, and scaling statistical and deep learning models.
• Experience with large-scale data (structured and unstructured), data management, parallel computing, and distributed systems.
• Ability to thrive with minimal supervision in a dynamic, fast-paced environment.
• Capability to understand diverse business processes and quickly contextualize data requirements.
• Strong problem-solving skills to translate business problems into actionable data strategies.
• Excellent communication skills (verbal and written) with a learning and innovation mindset.
• Strong passion for leveraging AI/ML to solve business problems and a proactive approach to experimentation.
• Hands-on experience with exploratory data analysis, machine learning, and advanced analytics methods.