Data Analyst

Responsibilities:
• Reporting: Automate the repetitive analysis and provide insights through dashboards. Work closely with the BI engineers to streamline the standard dashboards for the squads or business functions.
• Individual Contributor: This role is an individual contributor performing the below activities, and will not have anyone directly reporting.
• Data Horizon: Identify the new sources of data from your squad developments and work closely with the data engineers to orchestrate the data to the database, which can be used by other analysts or scientists.
• OKRs and KPIs: Work with Product managers of the squad to build upon the quarterly OKRs for the squad from an analytics perspective. Build dashboards to track the OKR progress with all the relevant KPIs. Contribute towards estimating the OKR target metrics for the squad.
• Impact Analysis: Conduct AB testing for all the new product features to assess the impact of the new feature. Conduct impact analysis on all the business initiatives to quantify the impact.
• Prescriptive analytics: Conduct research and basic statistical analysis to come up with recommendations for the product and business teams. This will help stakeholders evaluate trade-offs in different approaches, and create targets for driving business and product performance.
• The Data Analyst(Internally titled as DA-I) will be an integral part of our Tech teams, working as part of either the Product squads or Data squad.
• ROI Analysis: Conduct return on investment analysis on all the initiatives to evaluate the effectiveness of each initiative. Of the valuable initiatives, create the list of prioritization based on the magnitude of value the initiative brings to the product/business.
• Descriptive analytics: Conduct deep dive and root cause analysis to identify patterns, uncover opportunities, and create a shared understanding of insights with the stakeholders.
• Partnership: Partner closely with business stakeholders to identify and unlock opportunities, and with other data teams to improve platform capabilities around data modeling, testing platforms, data visualization, and data architecture.