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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.
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