Lead Data Insights Analyst

Role Overview

The candidate will collaborate closely with business users to understand their data needs, translate requirements into technical specifications, and deliver effective data solutions. The role includes performing root cause analysis, building dashboards, conducting business process assessments, and mentoring junior analysts.

Key Responsibilities Collaborate closely with business users to understand their data needs, translate requirements into technical specifications, and deliver data solutions. Perform root cause analysis on data discrepancies and implement data quality checks to ensure the integrity of data assets. Build highly impactful and intuitive dashboards that bring the underlying data to life through insights. Generate ad-hoc analysis for leadership to deliver relevant, action-oriented, and innovative recommendations. Conduct in-depth analyses of business processes, identify key levers in business and areas for improvement, and provide data-driven recommendations. Mentor and guide junior analysts, providing support and sharing best practices to enhance their skills and capabilities. Manage multiple tasks effectively, ensuring deadlines are met while maintaining high-quality deliverables. Design, implement, and analyze A/B experiments to test product changes and new features.

Skills Required 3+ years of relevant work experience as a Data Analyst Hands-on experience in SQL and Python Experience in data visualization tools such as Tableau Good aptitude and analytical skills Experience in statistical analysis and data modeling Demonstrated experience in data mining and cleansing, ETL data movement, and report and analysis automation/streamlining Experience working effectively with autonomy as well as within a team environment Understanding of Machine Learning concepts and willingness to learn Ability to zoom out for the bigger picture while working through the finer details

OKRs Objective 1: Enhance Data-Driven Decision-Making KR1: Increase the adoption of data-driven decision-making across the organization. KR2: Improve data quality and accuracy, resulting in a reduction in data-related errors and discrepancies. Objective 2: Drive Business Growth and Innovation KR1: Helping teams achieve incremental business growth through data-informed strategies and recommendations. KR2: Identify and prioritize new avenues of improvement opportunities through data analysis. Objective 3: Drive User Growth and Retention KR1: Working on a data-driven strategy to increase user retention and acquisition. KR2: Identifying issues and challenges through data and solving with the team. Objective 4: Creating Funnels for New Product Features Launch