Junior Data Analyst

Description

Job Summary: We are seeking a Junior Data Analyst to support strategic decision-making and ensure data quality at a sports betting and online gaming company. Key Highlights: 1. Data-driven work goes beyond generating reports, supporting strategic decisions 2. Develop and enhance dashboards for critical business metrics 3. Conduct descriptive, predictive, and prescriptive analyses to derive insights **ABOUT US** With over 10 years of experience, we are a 100% Brazilian company that combines the innovation of a young, dynamic team with the traditions that define us. Our focus is delivering exceptional experiences in the sports betting and online gaming sector, upholding ethics while consistently committing to quality and transparency for our customers. We are looking for a **Junior Data Analyst.** If you are just starting your career in data, eager to learn, curious, and enjoy working with information to support decisions, this opportunity is for you to join our team at **Aposta Ganha!** **Location:** Caruaru – On-site position **Employment type:** CLT **Working hours:** 9 AM to 6 PM, Monday to Friday Here, data work goes far beyond report generation. It means ensuring data quality, supporting strategic decisions, collaborating across multiple departments, and contributing to the performance of a brand operating at the fast pace of the digital world and sports betting. **Your responsibilities here:** * Develop, maintain, and enhance dashboards, ensuring clarity, consistency, and focus on critical business metrics. * Intensively use SQL for data collection, joining, cleaning, and validation in relational databases and data warehouses. * Actively identify anomalies (e.g., sudden drops, out-of-pattern variations, potential fraud, tracking issues, etc.) in revenue, conversion, engagement, and operational metrics. * Define, implement, and evolve monitoring triggers, bots, and automated alert and KPI-tracking routines (daily, weekly, and near real-time dashboards), rapidly signaling relevant deviations to responsible teams. * Conduct descriptive, predictive, and prescriptive analyses to understand customer behavior, products, campaigns, and operational performance. * Build customer segmentation, predictive models (e.g., churn, propensity, LTV, risk), A/B tests, and statistical decision-support models. * Support the dissemination of best practices in data usage, contributing to the organization’s analytical maturity. Requirements: **What we expect from you:** * Completed or ongoing degree in Computer Engineering, Information Technology, Data Science, Statistics, Economics, or related fields. * Experience as a Data Analyst or in a similar role. * Proficiency in SQL for complex queries, view creation, joins, aggregations, and large-volume data analysis. * Practical experience with Power BI (data modeling, DAX, measures, table relationships, dashboard performance). * Strong analytical and statistical capabilities, with ability to interpret results, test hypotheses, and explain metric fluctuations. * Knowledge of applied data science, including business metrics, experiment design (e.g., A/B testing), and fundamentals of statistical and predictive modeling. * Ability to clearly communicate insights to both technical and non-technical audiences. **You’ll stand out if you have:** * Postgraduate degree, MBA, or specialization in Data Science, Business Analytics, Statistics, Big Data, or similar (preferred). * Experience in iGaming, sports betting, gaming, e-commerce, or digital products with high-volume data. * Hands-on experience monitoring KPIs, generating periodic reports, and identifying anomalies. * Practical knowledge of a data analysis and data science programming language such as Python (pandas, numpy, scikit-learn) or R. * Experience with orchestration or metrics-monitoring tools (e.g., alerting tools, event or log monitoring). * Experience applying forecasting, scoring, clustering, or recommendation models to business contexts. * Familiarity with advanced statistics (confidence intervals, hypothesis testing, correlation, regression, time series). * Knowledge of best practices in experimentation (A/B testing, test & learn, incrementality).