Statistical Analyst | Forecasting Specialist

Role overview

Analysis and forecasting

• Collect, organize, validate, and analyze data from multiple business and operational sources.
• Identify trends, patterns, relationships, seasonal effects, cycles, anomalies, and significant changes.
• Forecast demand, sales, revenue, costs, capacity, and business performance using time-series and other models.
• Perform regression, correlation, hypothesis testing, and other statistical analyses; select methods suited to the question and data.
• Develop predictive models, scenarios, simulations, and sensitivity analyses to support decisions.
• Evaluate forecast accuracy, validate assumptions and outputs, monitor deviations, investigate variances, and compare actual results with forecasts.
• Prepare reports, dashboards, analytical summaries, and management presentations; turn findings into actionable recommendations.
• Support demand, inventory, financial, workforce, operational, and strategic planning.
• Improve data quality; automate analysis; partner with Data Engineering and IT on pipelines, reporting, and analytical infrastructure.
• Collaborate with stakeholders on objectives, assumptions, timelines, and outputs; refine models and document methodologies.

Required qualifications

• Bachelor’s degree in Statistics, Mathematics, Economics, Data Science, Finance, Business Analytics, or a related quantitative field.
• Proven experience in statistical analysis, forecasting, predictive analytics, business intelligence, or a related discipline.
• Strong knowledge of statistical methods, probability, data analysis, quantitative modeling, and time-series forecasting.
• Experience developing and evaluating predictive and forecasting models; regression, hypothesis testing, correlation, and statistical inference.
• Proficiency in Excel and experience with Python, R, SQL, SAS, SPSS, or similar tools.
• Ability to work with large datasets, clean and validate data, evaluate model performance, and conduct scenario, sensitivity, and variance analysis.
• Strong analytical and critical-thinking skills, attention to accuracy, and ability to communicate results and recommendations to non-technical stakeholders.

Preferred qualifications

• Power BI, Tableau, or equivalent data-visualization experience is advantageous.
• Experience with Finance, Sales, Operations, Supply Chain, Marketing, or Business teams is advantageous.
• Machine-learning or predictive-analytics experience, modern analysis tools, or relevant analytics certifications are beneficial.
• Strong project organization and ability to manage multiple analytical projects and deadlines.

What the employer offers

• Competitive salary and comprehensive employee benefits; salary amount and cadence are not specified.
• Exposure to forecasting, business intelligence, predictive analytics, data-driven decisions, modern analytical tools, and cross-functional projects.
• Professional development, technical and certification training, and opportunities to contribute to strategic planning and business optimization.
• Potential progression toward senior analyst, forecasting manager, data scientist, predictive analytics manager, or analytics leadership roles.