Data Analytics Analyst

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Job Category: Data

About Salesforce
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We are the Data, Analytics & Reporting team for the Revenue Operations (RevOps) organization. The core competency of Revenue Operations is managing Salesforce's Quote-to-Cash (Q2C) process. Our team mainly supports the Credit & Collections (also known as AR Operations) function in Revenue Operations, which consists of the Collections, Credit, Bad Debt, Cash Application, Customer Service, AR Technology, and AR Operational Excellence teams. Our mission is to deliver Business Intelligence and Data Solutions with speed, scale, and control while providing fuel for Salesforce's tremendous growth trajectory. We create accurate, timely and clear "data stories" and innovative solutions that deliver scale, efficiency and effectiveness for the operations supporting Salesforce's QTC and Operating Cash Flow (OCF). This role is hybrid and meets in office 3 days a week.

The Role:
The Business Intelligence / Data Science Analyst will primarily support Credit & Collections function in Revenue Operations, managing and driving the complete data lifecycle from data engineering to analysis and visualization. The role will have the opportunity, in partnership with the Business Intelligence Analyst, to shape and build the Data Engineering and Infrastructure pillar within the Credit & Collections function, as well influence process and policies across Revenue Operations and Finance. Additionally, the role will collaborate with partners across the organization and company to build Data and Analytics solutions for complex business processes, which includes automations, ETL data pipelines, etc. The role will also closely partner with business leaders to provide key BI support and ad-hoc analysis to help the leaders understand their business and provide guidance on areas of opportunities to meet key performance metrics and scale their operations. Lastly, the role will have the opportunity to build the Data Science function, in partnership with the Financial Reporting Lead, within the Credit and Collections function as well within the Revenue Operations organization.

Responsibilities:

• Data Engineering & Infrastructure: Drive data engineering within Credit & Collections and influence Revenue Operations and Finance policies.
• Data Science Development: Build data science capabilities for Credit & Collections and Revenue Operations.
• Cross-Functional Collaboration: Engage partners to identify challenges, define requirements, and deliver actionable solutions to complex business problems.
• Data Pipeline Design: Create secure, efficient data pipelines across systems.
• Sophisticated SQL Queries: Write advanced queries with multiple data sources and complex logic.
• Automated Process & Data Curation: Create repeatable automated processes and datasets that enable financial modeling, operations intelligence, and reporting of KPIs.
• Data Visualization: Design dashboards that deliver actionable insights.
• Business Intelligence Support: Provide key BI support and ad-hoc analysis to help business leaders understand their business, and provide guidance on areas of improvement and areas to focus to meet performance metrics.
• Process Improvement & Analytics: Design, develop and implement ad-hoc experiments and pilots to improve and scale the operations as well as provide relevant data and analytics solutions.
• Data Stewardship & Innovation: Become a master of your data universe; maintain data quality and validity, and explore innovative Salesforce solutions.

Desired Skills and Experience:

• Experience: 2-4 years in Data Analysis, Statistics, Computer Science, or related fields;
• Education: Bachelor's degree in Business Analytics, Statistics, or a quantitative field or equivalent experience.
• Programming Proficiency: Skilled in Python, R, and SQL for data pipelines and advanced analytics on large datasets.
• Data Visualization: Experience with tools like Tableau and Tableau CRM.
• Enterprise System Data Integration: Experience integrating data from systems, such as Oracle, Salesforce, Workday, or similar platforms.
• Statistical & ML Knowledge: Understanding of statistical models, predictive algorithms, ML/AI, NLP, and LLM is a plus.
• Process Optimization: Experience in process optimization, transformation, or automation.
• Analytical & Problem-Solving Skills: Strong analytical abilities with a fact-based, data-driven approach to problem-solving.
• Project & Time Management: Ability to handle various tasks and high-visibility projects with urgency and ownership.
• Communication & Collaboration: Clear and concise communication, with effective cross-functional project execution.
• Attention to Detail & Work Ethic: Highly organized, self-directed, resourceful, and dedicated to delivering high-quality work.
• Familiarity with Sarbanes Oxley and ASC 606 is a plus.

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