Note: The job is a remote job and is open to candidates in USA. SoTalent is hiring a Data Scientist, Enterprise Analytics to partner with business teams and use data science, machine learning, experimentation, and statistical modeling to support growth and strategic decision-making. The role develops analytical solutions, predictive models, experiments, metrics, and reporting to improve business outcomes and customer results.

Responsibilities

• Serve as a trusted analytics partner to business stakeholders, providing data-driven insights that support strategic planning and operational decision-making
• Collaborate closely with cross-functional teams to understand business objectives, identify opportunities, and develop analytical solutions that drive measurable outcomes
• Conduct exploratory data analysis to identify customer behaviors, performance trends, growth opportunities, and key factors influencing business success
• Translate complex and ambiguous business challenges into structured analytical frameworks, measurable hypotheses, and actionable recommendations
• Design, develop, validate, and deploy machine learning models to support customer acquisition, conversion, retention, expansion, and forecasting initiatives
• Build predictive models using advanced statistical and machine learning techniques such as classification, regression, clustering, and survival analysis
• Design and evaluate experiments, including A/B tests and quasi-experimental analyses, to measure the impact of business initiatives and product enhancements
• Develop and automate analytical workflows, reporting processes, and predictive solutions to improve scalability and efficiency
• Support the creation and maintenance of trusted business metrics, reporting frameworks, and self-service analytics capabilities
• Develop robust data models and ensure consistency, reliability, and accessibility of business-critical metrics and insights
• Write high-quality, maintainable SQL and Python code to support analytics, modeling, and data engineering requirements
• Participate in code reviews and promote analytical best practices, data quality standards, and scalable solution development
• Monitor model performance, evaluate results, and continuously improve analytical solutions based on business feedback and changing requirements

Skills

• 3–5 years of experience in Data Science, Business Analytics, Revenue Analytics, Go-to-Market Analytics, or a similar analytical role
• Strong ability to translate business questions into analytical approaches and communicate findings to technical and non-technical audiences
• Experience designing and interpreting experiments, including A/B testing, power analysis, causal inference, and performance measurement
• Strong understanding of statistical analysis, predictive modeling, and machine learning methodologies
• Advanced SQL skills and experience working with large-scale datasets in cloud-based data warehouse environments
• Experience developing dashboards, reports, and visualizations using business intelligence tools
• Proficiency in Python for data analysis, machine learning, automation, and statistical modeling
• Experience using data science libraries and frameworks for model development, feature engineering, and performance evaluation
• Strong problem-solving, analytical thinking, and data storytelling capabilities
• Ability to work independently while managing multiple priorities in a fast-paced environment
• Experience supporting Sales, Revenue Operations, Finance, Marketing, Customer Success, or other go-to-market functions
• Hands-on experience developing production-ready machine learning models and automated analytics solutions
• Knowledge of MLOps practices including model deployment, monitoring, retraining, version control, and workflow automation
• Experience with customer lifecycle analytics, growth analytics, customer retention, churn prediction, and expansion modeling
• Familiarity with product usage analytics, behavioral data analysis, and customer journey measurement
• Experience implementing AI-assisted workflows, intelligent automation, or advanced analytics solutions
• Knowledge of business performance metrics such as revenue growth, recurring revenue, customer retention, customer acquisition, and usage-based metrics
• Experience working in cloud-based data environments and modern analytics ecosystems

Benefits

• Remote (Continental U.S.) with occasional travel.

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