Data Analyst

Description :

About the Role

We are seeking a highly analytical and technically skilled Data Analyst to join our team in Bangalore. This role is central to our data-driven decision-making process, focusing on collecting, cleaning, and analyzing complex datasets to uncover key trends and deliver actionable insights that directly impact product, growth, and operational strategy. The ideal candidate has a strong technical foundation and is passionate about automating data pipelines and competitive research.

Responsibilities :

- Data Collection and Cleaning: Collect, query, and meticulously clean large, disparate datasets from various internal and external sources, ensuring data integrity, accuracy, and readiness for complex analytical modeling.

- Dashboarding and Reporting: Design, build, and rigorously maintain high-impact dashboards, reports, and trackers using modern Business Intelligence (BI) tools to monitor critical Key Performance Indicators (KPIs) across the entire business lifecycle.

- Competitive Intelligence: Conduct in-depth competitive benchmarking and market research by employing web scraping tools and techniques to gather external data (e.g., competitor pricing, product catalogs, market trends) for strategic analysis.

- Cross-Functional Collaboration: Proactively collaborate with Product, Growth, and Operations teams to identify critical business questions, formulate hypotheses, and provide data-backed, quantitative recommendations that drive measurable growth and optimization.

- Data Automation Development: Develop and maintain robust scripts and automation pipelines (e.g., using Python) to reliably extract, structure, and maintain external data such as pricing intelligence, product catalogs, and customer review data, ensuring timely and consistent updates.

- Performance Monitoring and Risk Flagging: Continuously monitor critical business KPIs, proactively identify performance deviations, flag potential risks or significant opportunities, and prepare concise reports to support executive and team decision-making.

- Insight Presentation: Translate complex analytical findings into clear, concise, and structured presentations and compelling data visualizations for various stakeholders, effectively communicating the story behind the data.

Requirements :

- Experience: 2-4 years of hands-on experience in business analysis, data analysis, financial analysis, or a similar quantitative role, preferably within the consumer tech, e-commerce, or high-growth startup sectors.

- Technical Proficiency: Expert-level proficiency in SQL for complex data querying, data manipulation, and optimization, along with strong skills in Excel or Google Sheets for modeling and ad-hoc analysis.

- BI Tool Mastery: Hands-on experience building and managing reports/dashboards using at least one industry-leading Business Intelligence (BI) tool such as Tableau, Power BI, or Looker.

- Analytical Mindset: Possess a strong analytical and statistical mindset, exceptional attention to detail, and a proven problem-solving orientation when facing ambiguous data or complex business challenges.

- Communication & Synthesis: Demonstrated ability to effectively translate complex data analyses and statistical findings into clear, actionable, and non-technical insights for diverse business audiences.

- Ownership & Adaptability: Comfortable taking full ownership of projects, managing tasks independently, and thriving in fast-paced, sometimes ambiguous operational environments.

Preferred Skills :

- Coding for Data: Proficiency in Python or R for data manipulation (Pandas, NumPy), statistical analysis, and developing automation scripts for data extraction and cleansing (e.g., using libraries like Beautiful Soup or Scrapy).

- Web Scraping Experience: Direct experience with implementing and maintaining production-grade web scraping solutions while adhering to ethical scraping practices.

- Knowledge of advanced statistical techniques (A/B testing, regression analysis, time-series forecasting) and their application to business growth experiments.

- Experience with cloud data warehousing solutions such as AWS Redshift, Google BigQuery, or Snowflake.

- Familiarity with product analytics tools (Mixpanel, Amplitude) for analyzing user behavior data.