Senior Associate - Data Analyst

As a Sr. Associate Data Analyst, you will leverage your 2-4 years of hands-on experience to analyze data, drive actionable insights, and optimize acquisition and activation strategies for paid marketing channels. You will collaborate with cross-functional teams and contribute to scaling key performance metrics across campaigns.

Role Specifics - Day in the Life

Campaign Analysis : Analyze performance metrics for paid marketing campaigns across Google Ads, Facebook, and other channels.

Insights Generation : Provide actionable insights to improve ROI and reduce CAC.

Attribution Tracking : Use tools like Google Analytics, Branch, and Meta Ads Manager to measure multi-channel performance and attribution.

Data Modelling : Build dashboards and visualizations to track KPIs like impressions, CTR, and conversion rates.

Collaboration : Work with marketing, product, and data engineering teams to align on campaign execution and measurement.

Optimization : Propose A/B tests, analyze results, and iterate strategies for funnel improvement.

Must-Have Skills

Experience : 2-4 years of hands-on experience in data analytics or marketing analytics.

Data Analysis Expertise : Proficient in Python and SQL for handling and analyzing large datasets.

Visualization Tools : Skilled in Power BI or Tableau for creating insightful dashboards.

Marketing Analytics Knowledge : Experience with tools like Google Analytics, Branch, and Meta Ads Manager.

Advanced Excel : Expertise in Excel, including pivot tables, VLOOKUPs, and formulas.

Data Pipelines : Basic knowledge of ETL processes for data extraction and transformation.

Problem-Solving : Ability to identify and resolve bottlenecks in marketing funnels.

Communication Skills : Strong presentation skills to convey insights to non-technical stakeholders.

Preferred Skills (Stand-Out Traits)

Certifications in tools like Google Analytics, Branch, or Facebook Blueprint.

Proven track record in optimizing paid marketing metrics such as CAC, CTR, and ROAS.

Experience with segmentation, cohort analysis, and activation tracking.

Advanced SQL proficiency, including complex queries and performance tuning.

Hands-on experience with cloud platforms like AWS Redshift.