Data Analyst

What the Candidate Will Do:

• Apply deep knowledge of basic statistics (significance testing, correlation analysis, confidence intervals, descriptive statistics) to support analytical solutions.
• Use statistical modelling techniques (regression, classification) to extract business value from campaign data.
• Utilize programming languages (Python, R, SQL), statistical packages (SciPy), and Google tools (Big Query, TensorFlow, Data lab) to prototype and deliver data-driven solutions.
• Recommend and develop technical solutions with guidance from senior leadership.
• Define project scope, setup, and effort estimation in collaboration with the account Analytics lead.
• Build and maintain strong relationships with Analytics leads and gain a deep understanding of client challenges.
• Work closely with key stakeholders to assess project needs and ensure delivery of best-in-class analytics work.
• Collaborate with regional leadership on process development, improvement, and compliance.
• Support campaign measurement, determine incremental lift from marketing activities, and manage reporting and data needs (ingestion, cleaning, delivery).
• Code in SQL and Python to create reports and build dashboards; automate recurring workloads to improve efficiency.
• Generate meaningful insights using advanced analytics/statistical techniques; create dashboards and presentations for wider teams.
• Ensure continuous collaboration and progression across bands, disciplines, and offices.

  Skills and Experience  

• 3–4 years of relevant industry experience in analytics-focused roles.
• Degree in an applied quantitative field (data science, mathematics, statistics, engineering, economics, business management, computer science, or related).
• Understanding of marketing campaigns, objectives, and measurement techniques; prior experience in digital agency or consulting preferred.
• Proficient coding skills in statistical software (R, Python, SciPy), programming languages (SQL, Python), and MS Office tools (especially advanced Excel/Google Sheets).
• Experience in owning and delivering analytics projects, including correlation, regression, significance testing, A/B tests, and supervised machine learning.
• Practical understanding of data science techniques, statistical analysis, and modelling.
• Passion for data analysis, troubleshooting data anomalies, integrating data from multiple sources to create repositories for data science models.
• Ability to transform raw data into actionable business insights for decision-making and strategic planning.
• Strong logical thinking, problem-solving, and stakeholder management skills.
• Excellent verbal and written communication skills.
• Adherence to quality standards and ability to plan and prioritize work.
• Experience using or building reports with business intelligence tools is a plus.
• Experience in applying big data, statistics, and analytical techniques to solve client problems is preferred.
• Business acumen to provide actionable strategic recommendations is preferred