Statistical Analyst | Forecasting Specialist

We are seeking a highly analytical Statistical Analyst | Forecasting Specialist to transform complex data into meaningful insights, statistical models, and reliable forecasts. This role combines statistical analysis, predictive modeling, forecasting, data interpretation, and business intelligence to support strategic planning, operational decision-making, and long-term business performance.

Collect, organize, validate, and analyze large datasets from multiple business and operational sources.

Develop statistical analyses to identify trends, patterns, relationships, and significant changes in data.

Build forecasting models to estimate future demand, sales, revenue, costs, capacity, and business performance.

Analyze historical data to identify seasonal patterns, trends, cycles, and anomalies.

Develop time-series forecasting models and continuously evaluate their accuracy.

Select appropriate statistical methodologies based on business questions and data characteristics.

Perform regression analysis, correlation analysis, hypothesis testing, and other statistical techniques.

Develop predictive models to support business planning and decision-making.

Evaluate forecast accuracy using appropriate statistical and business performance measures.

Monitor forecast deviations and investigate the underlying causes of significant variances.

Build scenarios and simulations to assess potential future outcomes under different assumptions.

Translate statistical findings into clear and actionable business recommendations.

Prepare forecasting reports, dashboards, analytical summaries, and management presentations.

Support demand planning, inventory planning, financial planning, workforce planning, and operational forecasting activities.

Analyze market, customer, sales, operational, and financial data to support forecasting initiatives.

Identify data quality issues and work with relevant teams to improve data accuracy and completeness.

Develop automated analytical processes to improve the efficiency and consistency of forecasting activities.

Collaborate with Data Engineering and IT teams to improve data pipelines, reporting systems, and analytical infrastructure.

Work with business stakeholders to define forecasting objectives, assumptions, timelines, and required outputs.

Conduct sensitivity analysis to understand how changes in key variables may affect forecasts.

Monitor external factors that may influence business forecasts, including market conditions, customer behavior, economic trends, and industry developments.

Compare actual results against forecasts and provide variance analysis.

Continuously refine forecasting models based on new data and changing business conditions.

Establish statistical and forecasting methodologies, documentation, and analytical standards.

Perform ad-hoc statistical analysis to support strategic projects and management decisions.

Validate model assumptions, outputs, and statistical significance before communicating findings.

Identify opportunities to improve forecasting accuracy through additional data sources, modeling techniques, or analytical approaches.

Support scenario planning and long-term strategic forecasting initiatives.

Communicate complex statistical concepts clearly to technical and non-technical stakeholders.

Stay current with developments in statistical modeling, forecasting techniques, machine learning, and analytical technologies.

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.

Strong understanding of time-series analysis and forecasting methodologies.

Experience with regression analysis, hypothesis testing, correlation analysis, and statistical inference.

Proficiency in Excel and experience with advanced analytical functions and modeling.

Experience using statistical or programming tools such as Python, R, SQL, SAS, SPSS, or similar technologies.

Knowledge of data visualization tools such as Power BI, Tableau, or equivalent platforms is advantageous.

Strong ability to work with large and complex datasets.

Experience cleaning, validating, transforming, and preparing data for analysis.

Understanding of forecasting accuracy…