Business Analytics - Sales & Marketing Analytics

Job Title: Business Analytics Intermediate Analyst - Sales and 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

1.        Technical Proficiency: Strong expertise in Python, Pyspark, and SQL for data analysis and manipulation.

2.        Data Presentation: Proficient in MS Excel and PowerPoint for data visualization, reporting, and presentation.

3.        Analytical Acumen: Demonstrated strong logical reasoning and problem-solving ability.

4.        Pattern Recognition: Proven proficiency in identifying trends and patterns within data.

5.        Communication: Strong written and verbal communication skills, with the ability to convey complex analytical concepts clearly to non-technical audiences.

6.        Analytical Methods: Extensive experience across different analytical methods, including hypothesis testing, segmentation, time series forecasting, and test vs. control comparison.

7.        Domain Expertise: Direct experience in Sales & Marketing analytics and campaign management.

Good to Have

1.        Machine Learning: Experience with predictive modeling using Machine Learning techniques.

2.        Unstructured Data Analysis: Experience with unstructured data analysis, such as call transcripts, using Natural Language Processing (NLP) or Text Mining.

3.        Industry Background: Experience in the financial services sector.

4.        Visualization Tools: Proficiency with Tableau or other data visualization tools.