Statistical Analyst | Forecasting Specialist

Role overview

Responsibilities

• Collect, validate, and analyze large datasets from business and operational sources; identify trends, patterns, relationships, seasonal effects, cycles, and anomalies.
• Build forecasting and time-series models for demand, sales, revenue, costs, capacity, and business performance; evaluate accuracy and refine models.
• Select statistical methodologies and perform regression, correlation, hypothesis testing, and other analyses; validate assumptions, outputs, and significance.
• Monitor forecast deviations, investigate causes, compare actual results with forecasts, and provide variance analysis.
• Develop scenarios and simulations, perform sensitivity analysis, and assess potential outcomes under different assumptions.
• Translate findings into business recommendations; prepare forecasting reports, dashboards, summaries, and management presentations.
• Support demand, inventory, financial, workforce, operational, and strategic forecasting; analyze market, customer, sales, operational, and financial data.
• Identify data quality issues and coordinate improvements to data pipelines, reporting systems, analytical infrastructure, and automated processes.
• Work with stakeholders to define objectives, assumptions, timelines, and outputs; establish and document forecasting methodologies and standards.
• Monitor external factors affecting forecasts and identify opportunities to improve accuracy through data, methods, and analytical approaches.

Requirements

• 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 forecasts and predictive models.
• Experience with time-series analysis, regression, hypothesis testing, correlation analysis, and statistical inference.
• Proficiency in Excel and experience with advanced analytical functions and modeling.
• Experience with Python, R, SQL, SAS, SPSS, or similar statistical or programming tools; the posting lists alternatives.
• Ability to work with complex datasets and prepare data through cleaning, validation, transformation, and other processes.
• Understanding of forecast accuracy metrics, model evaluation, scenario analysis, sensitivity analysis, and variance analysis.
• Ability to translate quantitative findings into practical recommendations and explain results to non-technical stakeholders.
• Power BI or Tableau experience is advantageous; machine learning, cross-functional business experience, and relevant certifications are beneficial.

What the employer offers

• Competitive salary and comprehensive employee benefits.
• Professional development, training, and support for relevant technical and professional certifications.
• Opportunities to work with forecasting methodologies, analytics technologies, cross-functional teams, and strategic planning initiatives.

Employment

• The description states Full-Time.