KEY RESPONSIBILITIES :
- Conduct detailed analysis on the performance of product features and assess the impact of product rollouts on business objectives.
- Utilize advanced business analysis techniques, including data projections, Profit & Loss (PnL) analysis, market trend analysis, and customer segmentation.
- Provide insights into product performance metrics including user engagement, churn rates, acquisition cost, and lifetime value (LTV).
- Work with cross-functional teams including product, engineering to define and refine product strategies based on data-driven insights.
- Create and modify Analytics Dashboards and Reports to track KPIs and business performance.
- Work with large datasets in MySQL, BigQuery, and other databases to fetch and analyze data relevant to product development and business goals.
- Develop and execute SQL queries to extract data for reporting and ad-hoc analyses.
- Collaborate with the data science team to integrate AI/ML models for predictive analytics and process automation.
- Identify trends, patterns, and anomalies from various data sources to provide business intelligence that drives product growth and operational efficiency.
- Lead data visualization efforts using tools like Tableau, Power BI, or Looker to communicate findings effectively to stakeholders.
- Provide actionable recommendations based on data insights to drive product and business decisions.
STAKEHOLDER MANAGEMENT :
SKILLS AND QUALIFICATIONS :
- 5+ years of experience as a Product and Business Analyst or in a similar analytical role with a strong focus on digital product analysis.
- Strong experience in conducting business analysis, including market research, data projections, financial forecasting, and PnL analysis.
- Advanced proficiency in SQL (MySQL, BigQuery) for complex data querying and data manipulation.
- Hands-on experience with data visualization tools such as Tableau, Power BI, or Looker.
- Proficiency in Python for data analysis, automation, and report generation.
- Familiarity with libraries like Pandas, NumPy, Matplotlib, and Seaborn is a plus.
- Experience with AI-driven tools and machine learning models to provide insights from data (e.g., integrating AI/ML tools into product strategies).
- Familiarity with tools like Google Analytics, Mixpanel, or Amplitude for tracking digital product metrics.
- Experience in using statistical tools and techniques for market analysis and customer insights (e.g., R, SPSS).
- Expertise in managing and analyzing large datasets and experience working with cloud platforms such as AWS, GCP, or Azure.
- Strong communication skills with the ability to present complex data insights in a simple and understandable manner to both technical and non-technical stakeholders.
- Experience working in an Agile or Scrum environment.
PERSONAL ATTRIBUTES :
- Analytical mindset, Agile Minded.
- Problem resolution skills , Team management skills.
- Ability to work under pressure and meet deadlines.
