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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