Data Analyst

Role & responsibilities

Key Responsibilities:

1. Data Extraction & Transformation:

• Use SQL to query large marketing databases (e.g., from Google Analytics, ad platforms, CRMs).
• Clean, transform, and prepare datasets using Python (Pandas, NumPy).

2. Marketing Analytics:

• Track performance of digital campaigns (SEO, SEM, social media, email marketing).
• Build marketing attribution models to understand ROI.

3. Dashboard & Reporting:

• Develop automated reports and dashboards using tools like Tableau, Power BI, or Python libraries (e.g., Plotly, Dash).
• Provide stakeholders with real-time insights.

4. Predictive Modelling & Insights:

• Build models for customer segmentation, churn prediction, LTV analysis, and campaign optimization.
• Use machine learning (e.g., scikit-learn, XGBoost) for targeting and personalization.

5. Cross-functional Collaboration:

• Work with marketing, product, and sales teams to define KPIs and optimize strategies.
• Translate business questions into data problems and communicate results clearly.

Typical Tools & Tech Stack:

• Languages:

  Python, SQL

• Libraries:

  Pandas, NumPy, scikit-learn, Matplotlib, seaborn

• Platforms:

  Google Analytics, Facebook Ads, HubSpot, Salesforce

• Visualization:

  Tableau, Power BI, Looker, or Python-based dashboards