Supply Chain Forecasting & Data Analyst
Savvital
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Benefits offered by this job
Job summary
Savvital is seeking a highly analytical Supply Chain Forecasting & Data Analyst to transform historical sales and order data into 12–18 month demand forecasts, inventory insights, and actionable business recommendations. You will clean and validate large datasets, identify demand patterns, and build models that drive decisions for stakeholders across the organization.
This role emphasizes building from raw data, forecasting methodology, and data-driven supply chain optimization rather than basic
Qualifications
- 3+ years of experience in supply chain analytics, demand forecasting, or related field.
- Hands-on experience with demand forecasting or supply planning.
- Advanced proficiency in Microsoft Excel.
- Strong experience with PivotTables, XLOOKUP/INDEX-MATCH, SUMIFS and advanced formulas.
- Experience extracting, cleaning, and analyzing data from ERP systems.
- Excellent written and spoken English.
Responsibilities
- Forecast demand and analyze patterns to develop SKU and customer forecasts.
- Build 12–18 month rolling forecasts.
- Create scalable Excel-based forecasting and inventory models.
- Perform data cleaning, validation, and quality checks on ERP data.
- Generate reports and present insights to non-technical stakeholders.
- Collaborate with stakeholders and own analytical projects.
Skills
Tools
Job description
Savvital is a forward-thinking organization that provides diversified services to small and medium-sized businesses in the international market, enabling them to build their future while benefiting from our customized solutions. Our team of educated experts are motivated individuals excited to handle tasks that add real capacity to a client's workday.
Our mission is to provide affordable solutions to growing companies through strategic task delegation. We envision creating an ecosystem that resonates with the human touch every business needs.
We are looking for a highly analytical Supply Chain Forecasting & Data Analyst to support a growing supply chain and distribution operation.
This is a hands-on analytical role focused on turning historical sales and order data into demand forecasts, inventory insights, and actionable business recommendations.
You’ll work with large transactional datasets and be responsible for cleaning and validating data, identifying demand patterns, building forecasting models, analyzing SKU and customer behavior, and translating your findings into recommendations that business stakeholders can understand and act on.
This is not a data-entry or basic reporting role.
We’re looking for someone who can take raw, imperfect data, figure out what it is telling us, determine the right analytical approach, and build a reliable model from the ground up.
Demand Forecasting & Analysis
- Analyze historical sales and order data to identify demand patterns and purchasing behavior.
- Develop SKU-level and customer-level demand forecasts.
- Build rolling 12 to 18-month demand forecasts using historical purchasing trends.
- Analyze year-over-year demand and growth patterns.
- Annualize year-to-date usage where appropriate.
- Identify consistent, seasonal, sporadic, declining, and growing demand patterns.
- Account for differences in units of measure, product categories, and customer purchasing behavior.
- Identify unusual changes in demand, including spikes, drops, and zero-usage products.
Excel Modeling
- Build scalable forecasting and inventory analysis models in Microsoft Excel.
- Use advanced Excel functionality to transform raw transactional data into meaningful insights.
- Develop formulas, calculations, PivotTables, lookups, and analytical logic to support forecasting.
- Create recommendation logic that can identify opportunities such as:
- Validate with Customer
- Increase Stocking
- Maintain Current Stocking
- Evaluate for Reduction
- Build exception reporting and alerts for products requiring additional review.
- Test forecasting methodologies on representative datasets before scaling them more broadly.
- Document formulas, assumptions, calculations, and methodology so models can be reviewed and maintained.
Data Management & Quality
- Extract, organize, clean, and validate large datasets from ERP and other business systems.
- Work with raw transactional data and identify inconsistencies, missing information, duplicates, and data-quality issues.
- Determine how data issues may impact forecasting and analytical results.
- Establish appropriate data-cleaning and validation processes.
- Communicate data-quality concerns clearly to relevant stakeholders.
Inventory & Supply Chain Insights
- Analyze demand trends to support inventory and stocking decisions.
- Identify SKUs that may require increased or reduced stocking levels.
- Evaluate customer purchasing behavior and its potential impact on inventory requirements.
- Identify products with declining, inconsistent, or unusual demand.
- Support inventory planning and replenishment decisions through data-driven analysis.
- Develop insights that help balance product availability with inventory efficiency.
Reporting & Business Insights
- Create clear and easy-to-understand reports showing historical usage, demand trends, forecasts, and recommendations.
- Translate complex analysis into practical commercial recommendations.
- Present findings in a way that can be understood by non-technical stakeholders.
- Highlight key trends, exceptions, risks, and opportunities rather than simply presenting raw numbers.
- Support the development of customer-facing inventory and demand reports.
Collaboration & Ownership
- Work independently while collaborating with business and supply chain stakeholders.
- Take ownership of analytical projects from raw data through final recommendations.
- Ask the right questions when requirements or datasets are unclear.
- Explain your analytical approach and reasoning clearly.
- Adapt forecasting methodology when business requirements or data patterns change.
- Communicate progress, challenges, and findings effectively.
- 3+ years of experience in supply chain analytics, demand planning, forecasting, inventory planning, operations analytics, or a closely related analytical field.
- Hands-on experience with demand forecasting and/or supply planning.
- Advanced proficiency in Microsoft Excel.
- Strong experience with:
- PivotTables
- XLOOKUP / INDEX-MATCH
- SUMIFS and advanced Excel formulas
- Data cleaning and transformation
- Trend analysis
- Growth-rate calculations
- Forecasting models
- Large datasets
- Experience extracting, cleaning, and analyzing data from ERP systems.
- Ability to build analytical models from raw transactional data rather than simply maintaining existing reports.
- Strong understanding of SKU-level demand and inventory concepts.
- Strong analytical reasoning and problem-solving skills.
- Ability to work independently with incomplete, inconsistent, or imperfect data.
- Strong written and spoken English.
- Ability to communicate analytical findings clearly to non-technical stakeholders.
Experience with any of the following would be an advantage:
- Microsoft Dynamics 365 Business Central
- Power BI
- Inventory optimization
- Demand planning
- Supply planning
- Sales & Operations Planning (S&OP)
- Manufacturing
- Wholesale or distribution
- Industrial supply chains
- Customer-level forecasting
- Inventory replenishment models
- Exception and anomaly reporting
- Customer-facing inventory or demand reporting
Experience working with ERP-generated sales-order data and building forecasting or inventory models from transactional data is particularly valuable.
Required:
- Microsoft Excel
Preferred:
- Microsoft Dynamics 365 Business Central
- Power BI
Experience with other ERP, BI, analytics, or cloud data platforms is also welcome.
We’re looking for someone who can do more than build spreadsheets.
The ideal candidate is someone who:
- Thinks analytically: Can look beyond the numbers and identify what they actually mean.
- Builds from scratch: Comfortable starting with raw data and developing a model independently.
- Questions the data: Doesn't automatically assume that every number is correct.
- Understands forecasting: Can explain why a particular methodology makes sense for a particular dataset.
- Thinks commercially: Understands how forecasts and demand patterns translate into inventory and business decisions.
- Communicates clearly: Can explain complex analysis without overwhelming stakeholders with technical details.
- Takes ownership: Can work independently without needing step-by-step instructions.
- Pays attention to detail: Understands that small data issues can lead to significant forecasting errors.
Within the initial engagement, you should be able to take raw sales and order history and build a reliable forecasting model that helps answer questions such as:
- What is this customer likely to purchase over the next 12-18 months?
- Which SKUs are trending upward or downward?
- Which products may require increased stocking?
- Which products may be overstocked based on declining customer usage?
- Which demand changes are unusual enough to require customer validation?
- What data or assumptions could affect the reliability of the forecast?
Success isn't simply producing an Excel workbook.
It means producing analysis that leads to clear, practical recommendations and giving stakeholders enough context to understand why those recommendations were made.
Were looking for candidates with genuine forecasting and analytical experience, but were more interested in what you have actually built and worked on than simply the title on your resume.
If you've personally built forecasting models, worked with large ERP datasets, analyzed customer or SKU-level demand, or turned raw transactional data into inventory recommendations, we want to hear about it.
Be prepared to walk us through a real example of your work, including:
What data you started with → how you cleaned it → how you analyzed it → how you built the model → how you validated it → what recommendation or business decision came from it.
- Base Salary: Market Competitive (determined by experience).
- Allowances: Premium Internet, Electricity, and Wellbeing allowances.
- Medical Insurance: Comprehensive health coverage.
- Growth: Annual performance-based increments and structured career progression.
- Bonuses: Individual performance and team-based target bonuses.
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