Data Analyst – Business Intelligence

Role Overview:
The Data Analyst will be at the forefront of data strategy and monetization, responsible for turning data into growth insights that drive business decisions, optimize performance, and unlock new revenue streams.

This role blends analytical depth, business intelligence, data engineering, and strategic thinking, ideal for professionals passionate about using data to fuel digital growth and audience value.

Key Responsibilities:

Data Analytics & Insights

• Collect, clean, and analyze data from multiple digital sources (web, app, CRM, marketing, and sales systems).
• Build automated dashboards and reports using tools like Power BI, Tableau, or Google Data Studio to track platform KPIs.
• Identify user trends, engagement drivers, and conversion patterns across verticals (classifieds, content, properties, jobs, cars, etc.).
• Generate actionable insights that support leadership decision-making and operational efficiency.
• Analyze marketing funnel performance and user acquisition metrics to identify growth opportunities.

Data Engineering & ETL

• Design, build, and maintain robust and scalable ETL pipelines to ingest and process data from a wide variety of sources, including web, app, CRM, marketing, analytics logs, and sales systems.
• Utilize both off-the-shelf and custom solutions (e.g., Azure Data Factory, custom Python scripts) to collect, transform, clean, and load data into our data warehouse, ensuring data quality, integrity, and accessibility.
• Develop a consolidated data architecture to support unified reporting, business intelligence, and advanced analytics.

Machine Learning & Predictive Modeling

• Design, develop, and deploy machine learning and predictive models to understand customer behavior, predict churn, and identify growth opportunities.
• Apply statistical analysis and modeling techniques to build frameworks for measuring user lifetime value, optimizing pricing strategies, and forecasting revenue.
• Implement A/B testing frameworks and conduct experiments to measure the performance of new features, marketing campaigns, and product changes.

Customer Data Platform (CDP) & Analytics

• Lead the development and implementation of a Customer Data Platform (CDP) to create a single, unified view of the customer journey.
• Integrate the CDP with our marketing and sales platforms to enable advanced audience segmentation, personalization, and targeted advertising.
• Attach machine learning models to the CDP to analyze customer behavior patterns, predict future actions, and deliver actionable insights to the business.

Monetization & Growth

• Develop data-driven monetization strategies, such as audience segmentation, advertising optimization, and data-based product offerings.
• Partner with Sales and Marketing teams to enhance campaign targeting, ad performance (CTR, CPC, CPM, ROAS), and audience segmentation, and cross-channel attribution
• Support pricing strategy and revenue forecasting through predictive analytics and business modeling.
• Build frameworks to measure subscription and user lifetime value.

Data Infrastructure & Governance

• Collaborate with Technology teams to ensure accuracy, integrity, and consistency of data across all systems.
• Establish and maintain clear KPIs, data definitions, and governance standards.
• Ensure compliance with ethical and legal standards for data usage.

Cross-Functional Collaboration

• Work with Marketing, Product, and Commercial teams to drive experiments (A/B tests) and measure performance outcomes.
• Present findings in a visually engaging and business-focused manner for executives and stakeholders.
• Translate analytical insights into actionable business recommendations.

Qualifications & Experience

• Education:
  Bachelor's or Master's degree in Data Science, Business Analytics, Statistics, Computer Science, Economics, or related field.
• Experience:
  5–8 years of experience in data analytics, business intelligence, data engineering, or growth analytics within a digital, e-commerce, or media technology company.
• Technical Skills:
• Strong knowledge of SQL, Python (pandas, numpy, matplotlib, scikit-learn), and BI tools such as Power BI, Tableau, or Google Data Studio.
• Experience with ETL/ELT tools (e.g., Azure Data Factory, Apache Airflow, or similar).
• Proficiency in machine learning and predictive modeling techniques for forecasting, customer behavior analysis, and LTV modeling.
• Experience with data warehousing solutions (e.g., Snowflake, BigQuery, Azure Synapse).
• Knowledge of Customer Data Platforms (CDP) and customer journey analytics.
• Experience with Google Analytics 4, BigQuery, or Looker is a plus.
• Business Skills:
  Proven track record in using data to enhance business performance, customer acquisition, retention, and monetization.
• Soft Skills:
  Strong communication, data storytelling, and cross-functional collaboration. Ability to translate complex data into simple insights.

Preferred

• Experience in audience segmentation, ad performance analytics, or subscription data modeling.
• Background in digital media, advertising, or marketplace platforms.
• Familiarity with data monetization models and creation of data-based products or reports.
• Hands-on experience implementing CDP solutions (e.g., Segment, mParticle, Adobe CDP, or similar platforms).
• Experience with cloud platforms (Azure, or GCP) for data infrastructure.
• Knowledge of A/B testing methodologies and experimentation platforms.