• Acts as a subject-matter expert of Engineering data (products, BOMs, materials, Documents, suppliers, etc.) • Gathers data from various sources, cleanse data for integrity and accuracy • Applies various data analysis tools to provide meaningful information and insights to help businesses make informed decisions • Providing technical expertise in database/data system development and data infrastructure setup • Collecting/consolidating data from various sources and organizing them into usable formats • Using statistical tools to derive meaningful information/insights from raw business data and analyzing data to find answers to specific questions • Assessing quality and meanings of data and cleansing corrupted data for integrity and accuracy • Creating data visualizations and reports for other stakeholders to comprehend business facts and trends to make better decisions • Working with relevant stakeholders to identify process improvement opportunities, propose system modifications, and devise data governance strategies • Creating appropriate documentation that allows others to understand data analysis processes and steps to foster wide adoption of data processing techniques • Liaising with various departments and internal stakeholders to create collaborative work relationships – understand their data requirements, propose the solutions, advocate the team values, obtain their supports when required.

• Track, analyze, and report on various marketing performance metrics, including Customer Acquisition Cost (CAC), New Arrivals, Subscriptions, Cancels, and Churns. • Develop and maintain the Lifetime Value (LTV) to CAC ratio models to ensure sustainable growth. • Monitor full-funnel conversion rates, identifying leakage points from awareness to conversion. • Identify trends and provide actionable insights to marketing and leadership teams to improve campaign efficiency and effectiveness. • Design and analyze A/B tests (split testing) for landing pages, ad creatives, and email subject lines to scientifically prove what works. • Perform cohort analysis to understand retention behaviors and predict future revenue. • Collaborate with the Data and Analytics team to ensure data integrity, maintain reporting dashboards, and support data-driven decision-making across the marketing function. • Manage the marketing attribution model to correctly assign value to different marketing channels (Paid Search, Social, Organic, Email).

• Own data collection strategies from start to finish - identifying what data we need, gathering information from various sources, and establishing data quality protocols. • Conduct thorough research to inform product decisions, pricing strategies, and market positioning. • Use SQL and Python to analyze data, discover patterns, and provide actionable insights that will guide business and product decisions. • Create comprehensive research reports and presentations to communicate findings to the team. • Work closely with developers to translate analytical findings into technical specifications for algorithm implementation. • Collaborate with the product team to ensure data collection and analysis align with business requirements.

• Analyze revenue and growth performance across Nift’s marketplace and auction systems • Partner with Sales to generate insights that explain auction behavior, pricing dynamics, and performance drivers for brands • Support Product and Data Science by measuring A/B tests, model calibration changes, and feature launches • Define, track, and report on core revenue and growth KPIs • Perform root-cause analysis on performance changes and anomalies • Translate complex analytical findings into clear narratives for internal stakeholders and client-facing use • Support stakeholder requests with timely, accurate analysis and clear recommendations • Ensure data accuracy, consistency, and trust across all analyses and deliverables