Head of Data Science

As the Head of Data at our company, you will have the responsibility to oversee and manage the data processes to ensure efficiency and accuracy. Your role will involve the following key responsibilities: - Design, develop, and optimize ETL/ELT pipelines for structured and unstructured data processing. - Maintain a modern data warehouse/lakehouse architecture. - Implement data partitioning, indexing, and performance tuning strategies for improved efficiency. - Establish robust cataloging, data quality rules, validation checks, and monitoring systems with a focus on data privacy and security guidelines. - Take ownership of business metrics from data extraction to analysis, hypothesis generation, structured analysis, and result evaluation. - Collaborate with stakeholders to define and implement key business metrics and establish real-time monitoring for critical KPIs. - Develop and maintain BI dashboards with automation for consistent and accurate reporting. - Conduct A/B testing, validate business hypotheses, and design analytical frameworks for product funnels and business operations. - Enable business teams with self-service reporting and data analysis capabilities. - Build and deploy predictive models such as churn prediction, demand forecasting, and fraud detection. - Partner with cross-functional teams to align analytics with business objectives. - Lead and mentor a high-performing analytics team, defining the analytics vision and strategy. Qualifications required for this role include: - 10-12 years of experience with at least 6 years in delivering analytical solutions in B2C consumer internet companies. - Bachelor's Degree in a data-related field such as Industrial Engineering, Statistics, Economics, Math, Computer Science, or Business. - Proficiency in Python, R, TensorFlow, PyTorch, and Scikit-learn. - Hands-on experience with AWS, GCP, or Azure for ML deployment. - Proven expertise in Power BI report development. - Experience in ETL pipelines, data modeling, and distributed systems. - Skill in supply chain processes, demand forecasting, time series models, and regression analysis. - Strong documentation skills and the ability to communicate complex technical concepts to non-technical stakeholders effectively.,