
Data Analyst (Remote - US) at Jobgether. This position is posted by Jobgether on behalf of a partner company. We are currently looking for a . Data Analyst. in the . United States. .. In this role, you will be a key contributor to the Revenue Analytics team, providing quantitative guidance to the Finance organization and supporting strategic decision-making across the company. You will maintain and refine predictive models, operationalize them into financial processes, and collaborate cross-functionally to uncover actionable insights on customer retention, revenue performance, and profitability. This position requires a strong analytical mindset, statistical expertise, and the ability to communicate findings to senior leaders. You will work with diverse datasets, build automated analytics tools, and partner closely with business stakeholders to drive data-informed decisions that improve overall organizational outcomes.. . Accountabilities:. Maintain and refine Lifetime Value (LTV) prediction models and integrate outputs into the revenue recognition process.. Collaborate with Finance, Product, Data Engineering, Revenue Operations, and Analytics teams to monitor data quality and model performance.. Act as the subject matter expert for LTV, forecasting components such as retention, commission, cash, revenue, and customer metrics.. Provide actionable insights into customer behaviors, churn, and retention trends for business stakeholders and senior executives.. Embed predictive analysis into revenue forecasting, profitability assessments, and ongoing performance optimization.. Create visualizations, reports, and storytelling materials to guide strategic business decisions.. . Bachelor’s degree in Mathematics, Statistics, Data Science, Analytics, or a related field (Master’s preferred).. 0–3 years of experience in data analytics, advanced analytics, or data science.. Experience with predictive modeling, customer behavioral analysis (LTV, churn, segmentation), and statistical methods including time series, decision trees, regression, and segmentation models.. Proficiency in Python and machine learning frameworks (e.g., Scikit-learn).. Strong experience with SQL, Excel, Tableau, and other data visualization tools; ability to work with diverse datasets and automate analytics workflows.. Excellent communication skills to translate technical results to non-technical stakeholders and senior leaders.. Strong project management, multitasking, and attention to detail.. Preferred: Knowledge of eCommerce, digital marketing, Fintech, Insurtech, Finance, and Accounting metrics.. . Company Location: United States.