Marketing Analyst

Job Overview

The job requires understanding the business and framing the business requirement as a data analytics problem statement. The individual will be responsible for providing business insights and managing end-to-end project delivery. The job requires building relationships with the client and presenting work directly to clients. The individual should effectively collaborate with team members around problem structuring and use of analytics (tools and techniques) to carry out analysis. The individual will be responsible for project delivery and gathering client feedback.

Key Responsibilities:

• Lead and manage analytics projects focused on banking/financial sectors.
• Marketing analytics experience, managed and optimized marketing campaigns
• Utilize strong Python skills to develop analytical models and tools.
• Collaborate with cross-functional teams to identify business challenges and deliver actionable insights.
• Engage with clients to understand their needs, present findings, and recommend solutions.
• Oversee project timelines, budgets, and resources to ensure successful project delivery.
• Mentor and guide junior team members in analytics methodologies and tools.
• Stay updated on industry trends and best practices to enhance service offerings.

Qualifications:

• Bachelor's degree in a related field (e.g., Computer Science, Data Science, Business Analytics).
• Minimum 6+yrs of experience
• Approximately 2 years of experience in banking analytics and/or marketing analytics.
• Strong proficiency in Python for data analysis and/or model development.
• Excellent problem-solving skills with a proven ability to tackle complex business challenges.
• Experience in client management and effective presentation of analytical findings.
• Strong project management skills with a track record of delivering projects on time and within budget.
• Exceptional communication skills, both written and verbal.

Preferred Skills:

• Comprehensive marketing experience from targeting, campaign execution, insight generation through a measurement framework and subsequent optimization skill is good to have
• Experience with exploratory data analysis, feature engineering, pivots, and data summarization is required.
• Understanding basic statistical techniques like t-tests, chi-square tests, hypothesis testing, A/B testing, regression analysis, etc.
• Familiarity with statistical analysis and machine learning concepts.
• Understanding of banking and financial services.
• Experience of programing in PySpark is good to have.
• Experience with data visualization tools (e.g., Tableau, Power BI).