Quantium - Lead - Data & AI Scientist

Job location: [{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bangalore","addressCountry":"IN"}}] Work arrangement: Employment type: FULL_TIME Salary: "" Experience requirements: {"monthsOfExperience":96,"educational":{"credentialCategory":"bachelor degree"}} Education requirements: "" Experience and Qualifications: Technical Foundation: - 8+ years of experience in data science or analytics roles, with readiness to take on coordination and leadership responsibilities - Strong experience with Python and SQL for data analysis and solution development - Good experience with cloud platforms (e.g. GCP, Azure, AWS) and cloud-based analytics tools - Solid understanding of data science methods, statistical approaches, and their practical application in commercial contexts - Familiarity with analytics and delivery best practices, and interest in helping others apply them AI-Native Capability: - Transformation across a portfolio. You've driven AI adoption or workflow change across a set of assets or a team's ways of working, with targets and tracking. You can describe what you set out to change, what actually moved, and what stalled - Still hands-on. Active, current use of AI coding and analytics tools such as Claude, Claude Code, Cursor, or GitHub Copilot, to the point where you can sit with a senior engineer, look at their agent setup, and have a useful opinion - Working understanding of how multi-step agentic workflows are built, evaluated, and maintained: context design, tool definitions, evaluation loops, failure recovery, and human checkpoints - Awareness of what agentic pipelines cost to run and maintain, including token spend, run time, and review burden, and the point at which automation costs more than it saves - Ability to frame AI capability to senior stakeholders in outcome terms such as cycle time, capacity released, quality, and risk, rather than tool adoption counts Readiness for Management: - Interest in supporting and developing others (formal management experience is welcome but not required) - Good communication and collaboration skills for working with diverse team members across cultures, time zones, and experience levels - Willingness to learn management skills including goal-setting, feedback, and performance conversations - Openness to developing your own leadership style with guidance and support - Comfort holding accountability for outcomes owed to stakeholders in other countries, including escalating and pushing back when needed Problem-Solving & Adaptability: - Systematic approach to problem-solving with ability to coordinate complex technical work - Ability to balance technical involvement with team coordination and AI transformation responsibilities - Commercial understanding, or willingness to develop the business context behind analytics work - Adaptability and resilience in a rapidly changing technical environment, particularly comfort with the pace of AI evolution Education & Background: - Degree in engineering, mathematics, statistics, computer science, physics, or a related quantitative field, or equivalent demonstrated capability What Would Be Great to Have: - Experience mentoring, training, or leading teams - formal or informal - Coordinate the development of analytics solutions across product initiatives, ensuring quality and consistency in technical approaches - Retail analytics background, or client-facing consulting experience across other industries (e.g. financial services, government, health) - Previous exposure to product development environments or cross-functional collaboration - Experience working across different cultures or in distributed teams - Understanding of data governance, privacy considerations, and ethical AI practices