Growth Analytics Assistant Manager, Manager

Role Overview: As a Data Analyst within the Growth team, your primary responsibility is to drive data-based problem solving by closely collaborating with business teams. Your role involves understanding growth challenges, translating them into analytical problems, and delivering insights that enhance acquisition, engagement, and retention for the app and loan products. You will be conducting in-depth hands-on analysis across multiple data sets to support data-driven decision-making. Key Responsibilities: - Partner with Growth and Product teams to comprehend key challenges and priorities, translating business goals into measurable analytical problems that directly influence strategy and execution. - Lead analytical projects and develop dashboards for app installs, user funnel analysis, and marketing performance evaluation. - Construct models to identify user behavior such as likelihood to install, churn, or uninstall the app. - Conduct exploratory analysis to identify new opportunities, generate hypotheses, and assess potential upsides swiftly. - Collaborate with data engineering to create and implement new analytical tools and enhance the data infrastructure. - Analyze, forecast, and generate custom reports to provide key performance indicators and insights company-wide. - Develop and refine propensity models to predict high-conversion and high-value user cohorts. - Recommend targeting strategies, timing, and communication approaches to enhance performance. - Analyze campaign and channel data to optimize marketing ROI and reduce acquisition costs. - Determine optimal channels, timing, and frequency for customer engagement. - Support experiments and A/B tests to validate marketing strategies. Qualifications: - B.Tech from a Tier-1/Tier-2 institute with 4-5 years of experience. - MBA is considered a plus. Additional Details: You should possess 4-5 years of proven experience in numbers-driven and analytical marketing environments, preferably in an online consumer business or a Bank/NBFC. Strong data handling, interpretive, and problem-solving skills are essential, with the ability to process large volumes of transaction-level data and derive actionable results efficiently. Proficiency in R/Python, SQL, Tableau, and Advanced Excel, including Pivot Tables, is required for this role.,