
Director – Data Science
3 weeks ago
Job Title: Director Data Science
Location: Bangalore
Experience: 8+ years
Job Details:
We are seeking a highly experienced and strategic Director Data Science to lead our data science organization. The role requires a visionary leader who can design, build, and scale advanced data solutions to drive business growth, product innovation, and operational excellence.
Educational Qualifications:
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field from a top-tier engineering college is required.
Must have Technical Skills:
- 8+ years of professional experience in Data Science/ML/AI, with at least 3 years in a leadership/people management role.
- Proven expertise in statistical modeling, machine learning, deep learning, NLP, and data mining.
- Strong experience with Python, R, SQL, Spark, TensorFlow, PyTorch, and big data ecosystems.
- Hands-on experience in building and deploying large-scale ML models in production.
- Exceptional leadership, communication, and stakeholder management skills.
- Ability to translate complex data insights into clear, actionable business strategies.
- Strong understanding of cloud platforms (AWS, Azure, GCP) and modern data stack.
- Advanced degree (Master's/Ph.D.) in Computer Science, Data Science, Mathematics, Statistics, or related field.
Key Responsibilities:
- Define and drive the overall data science vision, strategy, and roadmap aligned with organizational goals.
- Lead and mentor a high-performing team of Data Scientists, ML Engineers, and Analysts.
- Design and implement end-to-end machine learning and AI solutions, from data exploration to deployment.
- Collaborate with C-suite executives, product leaders, and engineering teams to translate business needs into data-driven insights and strategies.
- Drive innovation in NLP, recommendation systems, predictive analytics, computer vision, and generative AI to enhance products and services.
- Establish best practices for data governance, model validation, and ethical AI adoption.
- Own and deliver measurable outcomes, including revenue growth, cost optimization, and customer engagement improvements.
- Stay updated with emerging technologies, tools, and trends to ensure continuous innovation.
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