Statistical Analyst | Forecasting Specialist

Role Overview

Analysis and Forecasting

• Collect, organize, validate, and analyze large datasets from multiple business and operational sources.
• Identify trends, patterns, relationships, significant changes, seasonal patterns, cycles, and anomalies.
• Build forecasts for future demand, sales, revenue, costs, capacity, and business performance.
• Develop and evaluate time-series forecasting models; select statistical methods suited to business questions and data.
• Perform regression, correlation, hypothesis testing, statistical inference, and other statistical techniques.
• Develop predictive models, scenarios, simulations, and sensitivity analyses to support business planning.
• Evaluate forecast accuracy, monitor deviations, investigate significant variances, compare actuals with forecasts, and refine models as conditions change.

Reporting and Collaboration

• Translate statistical results into actionable business recommendations and prepare forecasting reports, dashboards, analytical summaries, and management presentations.
• Support demand, inventory, financial, workforce, operational, and long-term strategic planning.
• Analyze market, customer, sales, operational, and financial data; monitor external factors that may influence forecasts.
• Identify data-quality issues and work with teams to improve data accuracy and completeness.
• Automate analytical processes and collaborate with Data Engineering and IT to improve pipelines, reporting systems, and analytical infrastructure.
• Define forecasting objectives, assumptions, timelines, and outputs with stakeholders; communicate complex statistical concepts to technical and non-technical audiences.
• Establish documented statistical and forecasting methods and standards, validate assumptions and outputs, and conduct ad hoc analysis for strategic decisions.
• Stay current with statistical modeling, forecasting, machine learning, and analytical technologies.

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, and quantitative modeling.
• Experience developing and evaluating forecasting and predictive models, including time-series analysis.
• Experience with regression analysis, hypothesis testing, correlation analysis, and statistical inference.
• Proficiency in Excel, including advanced analytical functions and modeling.
• Experience using at least one statistical or programming tool such as Python, R, SQL, SAS, SPSS, or similar.
• Ability to handle complex datasets, prepare data for analysis, evaluate forecast accuracy, and conduct scenario, sensitivity, and variance analysis.
• Strong analytical and critical-thinking skills, attention to detail, communication, presentation, and project organization skills; able to manage multiple projects and deadlines.

Advantageous Experience

• Knowledge of Power BI, Tableau, or equivalent visualization tools is advantageous.
• Experience with Finance, Sales, Operations, Supply Chain, Marketing, or Business teams is advantageous.
• Experience with machine learning, modern data-analysis technologies, or relevant statistics, analytics, forecasting, or business-intelligence certifications is beneficial.

What the Employer Offers

• Competitive salary and comprehensive employee benefits.
• Exposure to advanced forecasting, business intelligence, predictive analytics, and data-driven decision-making.
• Professional development, training, and support for relevant technical and professional certifications.
• Cross-functional work and opportunities to contribute to strategic planning and business optimization.
• Career progression opportunities toward senior analyst, forecasting manager, data scientist, predictive analytics manager, or head of analytics roles.