Manager Data Science

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Experience: 7+ yrs

Location: India

As a Manager Data Science, you will spearhead the development and execution of advanced analytical strategies that drive business insights and operational excellence across multiple domains. You will lead a cross-functional team of data scientists, analysts, and engineers, translating complex data challenges into robust, scalable solutions that impact key decision-making processes. Your role will involve setting the vision for probability-based modeling, statistical inference, and machine learning initiatives, while ensuring rigorous practices in time series forecasting and Bayesian analysis. You will collaborate with stakeholders to prioritize projects, guide model deployment, and measure performance, all while maintaining high standards of data integrity and compliance.

Requirements

• Lead the design, development, and deployment of predictive models using machine learning and statistical techniques.
• Oversee end-to-end data science projects, from hypothesis generation to production-grade solution delivery.
• Drive the adoption of Bayesian methods to enhance probabilistic inference and decision-support systems.
• Mentor and coach a team of data scientists, fostering a culture of continuous learning and innovation.
• Collaborate with product, engineering, and business leaders to translate data insights into actionable strategies.
• Develop and maintain robust reproducibility frameworks, ensuring model transparency and auditability.
• Champion the use of advanced time series techniques for demand forecasting, anomaly detection, and trend analysis.
• Integrate operations research methodologies to optimize complex logistics, supply chain, or resource allocation problems.
• Establish performance metrics and monitoring dashboards to evaluate model efficacy and business impact.
• Stay abreast of emerging trends in data science, statistical modeling, and AI, and recommend their application to the organization.
• Proven experience (7+ years) leading data science teams and delivering high-impact analytical solutions.
• Deep expertise in probability theory, statistical inference, and machine learning algorithms.
• Strong background in Bayesian data analysis for predictive modeling and decision-making.
• Proficiency in time series forecasting, including ARIMA, Prophet, and state-space models.
• Hands-on knowledge of operations research techniques such as linear programming, MIP, and simulation.
• Advanced programming skills in Python, R, or similar, with experience in scalable data pipelines.
• Demonstrated ability to translate complex analyses into clear, actionable business recommendations.
• Excellent communication and stakeholder management skills across technical and non-technical audiences.
• A track record of mentoring junior talent and building high-performing analytics teams.
• Passion for continuous learning and staying current with cutting-edge research and industry best practices.