Sales Operations Data Scientist

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sales Operations Data Scientist based in the United States. This role offers the opportunity to turn complex commercial and customer data into insights that shape business strategy and accelerate growth. You will go beyond reporting on what happened to understand why it happened, predict future behavior, and uncover new opportunities. Working closely with sales, marketing, finance, product, and other teams, you will build trusted analytics that support smarter decision-making. You will own projects end-to-end, from data extraction and cleaning through statistical modeling, visualization, and actionable recommendations. The role also offers the chance to establish scalable data practices, improve data quality, and automate recurring reporting. You’ll join a growing, collaborative environment where curiosity, continuous learning, and innovative thinking are highly valued. Define, develop, and maintain KPIs that measure product health, customer engagement, commercial performance, and marketplace dynamics. Analyze customer behavior, product usage, and business trends to identify risks, opportunities, and drivers of future performance. Translate complex analytical findings into clear, actionable recommendations for product, commercial, and leadership teams. Partner cross-functionally with teams including sales, marketing, finance, HR, and product to identify business questions and deliver data-driven solutions. Collect, clean, transform, and analyze large datasets from internal and external sources, ensuring the accuracy and integrity of analytical outputs. Develop predictive models and statistical analyses that help explain business behavior and inform strategic decisions. Build and automate recurring reports and analytical processes to improve efficiency, consistency, and timeliness. Improve data accessibility and quality by supporting scalable data solutions, ETL processes, and data architecture. Monitor and optimize data pipelines and data quality while identifying opportunities for continuous process improvement. Implement and maintain appropriate data governance, security, and quality controls across data workflows. Develop clear data visualizations and dashboards that make complex information accessible and actionable for diverse stakeholders. Help foster a culture of data-driven decision-making and continuous improvement across the commercial organization. Requirements Minimum of 8 years of experience as a Data Scientist, Data Analyst, or in a closely related analytics-focused role, with demonstrated impact on business strategy and decision-making. Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, or a related technical discipline; an advanced degree or relevant certification is a plus. Strong proficiency in SQL and at least one high-level programming language such as Python, R, Scala, or Java. Demonstrated expertise in statistical analysis, predictive modeling, data extraction, data cleaning, and data visualization. Experience working with large datasets and translating analytical findings into practical business recommendations. Strong understanding of product and customer analytics, with the ability to identify meaningful patterns, trends, risks, and opportunities. Experience with ETL processes and data engineering concepts; exposure to Azure cloud services or Microsoft Fabric is a plus. Experience with data visualization platforms such as Power BI is preferred. Ability to work effectively with cross-functional stakeholders, particularly across sales, marketing, finance, HR, and product functions. Strong communication skills, with the ability to explain complex technical and analytical concepts clearly and concisely to both technical and non-technical audiences. High level of accountability, curiosity, adaptability, and commitment to continuous learning. Comfortable