Data Analytics (Stock Borrowing & Lending)

Responsibilities

• Develop and lead the data analytics, automation, and monitoring strategy and roadmap in alignment with business objectives.
• Lead and develop a high-performing team of data analysts and engineers, ensuring quality, efficiency, and technical excellence.
• Partner with senior management and cross-functional stakeholders to identify business opportunities and translate business requirements into data-driven solutions.
• Oversee end-to-end delivery of analytics and automation initiatives, from strategy and scoping through implementation, deployment, and ongoing support.
• Lead the application of statistical, forecasting, time-series, anomaly detection, and experimental methodologies to support business decision-making.
• Establish and monitor key performance indicators to measure business impact and the effectiveness of analytics initiatives.
• Manage relationships with local and global stakeholders, including client-facing onboarding and implementation for strategic initiatives.
• Drive continuous improvement through the adoption of data, automation, AI, and emerging technologies.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related quantitative discipline.
• Minimum 5 years of relevant experience in data analytics, data science, business intelligence, or a related field, with proven experience in project or team leadership.
• Strong proficiency in Python and SQL.
• Hands-on experience with BI and data visualization tools, such as Power BI, Tableau, Metabase, Looker, or Grafana.
• Experience with workflow automation and data orchestration tools, such as Power Automate, Power Apps, Airflow, dbt, or equivalent.
• Strong knowledge of statistics, experimental design, A/B testing, forecasting, time-series analysis, and anomaly detection.
• Proven ability to translate complex business requirements into practical, scalable, and measurable data-driven solutions.
• Strong analytical, problem-solving, communication, stakeholder management, and leadership skills.
• Experience in coaching and mentoring data analytics or engineering professionals.