Data Analyst

Candidates typically face a three‑stage process: an online aptitude test, a technical interview focusing on SQL queries, Python scripting, data visualisation and case‑study analysis, followed by an HR round assessing cultural fit and communication. The difficulty is moderate; strong fundamentals in data manipulation and clear problem‑solving approaches are key. Preparing with real‑world ad‑tech scenarios and practising dashboard creation can give a distinct advantage.

GreedyGame promotes an impact‑driven culture where every insight can shape product and revenue decisions. Employees benefit from flexible hybrid schedules, regular mentorship sessions and generous upskilling stipends. The company emphasizes work‑life balance while encouraging rapid learning and ownership of high‑visibility projects.

Bachelor's degree in Computer Science, Information Technology, Electronics, Statistics, Mathematics or related field; Minimum 60% aggregate (or CGPA 6.0/10); Fresh graduates of 2025‑2027 batches; No active backlogs at the time of joining; Strong analytical mindset and willingness to learn.

Round 1: Online aptitude test (logical reasoning, quantitative & data interpretation) → Round 2: Technical interview (SQL queries, Python coding, data visualisation, case study) → Round 3: HR interview (cultural fit, career goals, communication skills)

GreedyGame is a fast‑growing technology company that sits at the crossroads of digital advertising, mobile monetisation and data science. Founded in 2014, the firm has built a suite of data‑driven platforms that help app developers maximise revenue through intelligent ad placement, real‑time bidding and behavioural analytics. With a client base that spans global brands and thousands of mobile apps, GreedyGame leverages machine learning, big‑data pipelines and sophisticated analytics to turn raw user interactions into actionable business insights. The company’s culture is rooted in rapid experimentation, cross‑functional collaboration and a relentless focus on impact, making it an attractive destination for fresh talent eager to work on cutting‑edge ad‑tech solutions. The Data Analyst role is designed for recent graduates who are passionate about turning data into strategic decisions. As a member of the analytics team, you will work closely with product managers, engineers and marketing specialists to design, build and maintain data pipelines, create visual dashboards, and uncover growth levers that directly influence revenue. This position offers a blend of technical depth – working with SQL, Python, BigQuery and ETL tools – and business acumen – interpreting ad‑performance metrics and recommending optimisation strategies. Key Responsibilities: 1. Design, develop and maintain scalable data pipelines to ingest, clean and transform structured and unstructured data from multiple ad‑tech sources. 2. Build interactive dashboards and visualisations using Power BI or Tableau to monitor KPIs such as fill‑rate, eCPM, user engagement and revenue trends. 3. Conduct deep‑dive analyses to identify anomalies, growth opportunities and optimisation recommendations across campaigns, geographies and device segments. 4. Collaborate with product and engineering teams to define data requirements, validate model outputs and support A/B test design and analysis. 5. Automate recurring reports and data extracts using SQL, Python or R, reducing manual effort and improving data accessibility for non‑technical stakeholders. 6. Document data dictionaries, lineage and business logic to ensure consistency and promote data literacy across the organisation. 7. Participate in code reviews and data quality audits to maintain high standards of data integrity. 8. Stay updated with emerging analytics tools and industry best practices, proposing enhancements to the existing tech stack. 9. Support ad‑operations and sales teams with ad‑hoc queries and insight generation during high‑stakes campaign periods. Tech Stack: SQL, Python, BigQuery, Google Analytics, ETL concepts, Power BI/Tableau, Looker (preferred), Apache Airflow (preferred), Excel (advanced functions & PivotTables), statistical modelling (regression, clustering). Growth Path: Starting as a Junior Data Analyst, high performers can progress to Senior Analyst, Analytics Lead, and eventually to Product Analytics Manager or Data Science roles, with ample mentorship, upskilling stipends and exposure to advanced machine‑learning pipelines. Why Join GreedyGame? You will work on real‑world ad‑tech challenges that affect millions of users, enjoy a hybrid work model with flexible hours, receive mentorship from seasoned data professionals, and be part of a culture that rewards curiosity, impact and continuous learning.