Business Analytics - Sales & Marketing Analytics

Overview

We are seeking a highly motivated and skilled Business Analytics Intermediate Analyst with a specialized focus on Sales and Marketing analytics. The ideal candidate will be instrumental in transforming complex data into actionable insights, driving strategic decision-making, and optimizing our sales and marketing efforts. This role requires a strong analytical mindset, proficiency in various analytical techniques, and excellent communication skills to articulate findings to diverse stakeholders.

Responsibilities

• Utilize Python, Pyspark, and SQL to extract, manipulate, and analyze large datasets, to deliver on sales and marketing opportunities and track performance.
• Apply strong logical reasoning and problem-solving skills to address complex business challenges within the sales and marketing domain.
• Identify significant trends, patterns, and anomalies within sales and marketing data to uncover opportunities and risks.
• Conduct in-depth analyses using a variety of analytical methods, including hypothesis testing, customer/market segmentation, time series forecasting, and test vs. control comparisons.
• Develop clear, concise, and impactful presentations using MS Excel and PowerPoint to communicate analytical findings and recommendations to business leaders.
• Collaborate with sales and marketing teams to understand their analytical needs and deliver insights that support their strategic goals.
• Contribute to the continuous improvement of analytical methodologies and data reporting processes.

Qualifications

Must Have

• Propensity modelling
• Market mix modelling
• Sales & Marketing effectiveness
• Cross-sell, up-sell strategy
• Design Acquisition, Retention, Reactivation strategy
• Loyalty program management & Redemption analytics
• CLTV

Technical Proficiency: Strong expertise in Python, Pyspark, and SQL for data analysis and manipulation. Data Presentation: Proficient in MS Excel and PowerPoint for data visualization, reporting, and presentation. Analytical Acumen: Demonstrated strong logical reasoning and problem-solving ability. Pattern Recognition: Proven proficiency in identifying trends and patterns within data. Communication: Strong written and verbal communication skills, with the ability to convey complex analytical concepts clearly to non-technical audiences. Analytical Methods: Extensive experience across different analytical methods, including hypothesis testing, segmentation, time series forecasting, and test vs. control comparison. Domain Expertise: Direct experience in Sales & Marketing analytics and campaign management.

Good to Have

Machine Learning: Experience with predictive modeling using Machine Learning techniques. Unstructured Data Analysis: Experience with unstructured data analysis, such as call transcripts, using Natural Language Processing (NLP) or Text Mining. Industry Background: Experience in the financial services sector. Visualization Tools: Proficiency with Tableau or other data visualization tools.