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Senior/Lead - Data Scientist

ProGrowth People SolutionsBangalore
SENIOR_LEVELLead
👁️ 0 views📝 0 applicationsPosted 9/8/2026Expires 10/14/2026
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Job Description

Senior / Lead Data Scientist Experience: 10 - 15 Years Employment Type: Full-Time Location: Bangalore / Willing to move to Dubai About the Role: We are looking for an experienced Senior / Lead Data Scientist with 10 - 15 years of experience to lead data science initiatives and build high-impact AI/ML solutions across the business. The ideal candidate will combine strong technical expertise with business understanding and leadership capabilities. You will be responsible for identifying high-value opportunities, defining the data science roadmap, leading complex analytical and machine-learning projects, and working closely with senior leadership, product, technology, and business teams. Key Responsibilities: Data Science & AI Strategy: - Define and drive the organization's Data Science, AI, and Machine Learning roadmap . - Identify opportunities where data and AI can create measurable business impact. - Translate complex business problems into scalable data science solutions. - Establish best practices around modelling, experimentation, validation, deployment, and monitoring. - Evaluate emerging AI/ML technologies and identify opportunities for adoption. Qualifications: - Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics , or a related quantitative discipline. - 10 - 15 years of relevant professional experience. - Demonstrated track record of taking data science solutions from problem definition - modelling - deployment - measurable business impact . What Success Looks Like: - Building and executing a strong Data Science and AI roadmap. - Delivering measurable improvements in revenue, customer experience, retention, and operational efficiency. - Developing scalable ML/AI solutions used in production. - Building and mentoring a high-performing Data Science team. - Increasing adoption of data-driven decision-making across the organization. - Establishing robust data science and MLOps practices.

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