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Savvital
Savvital
51 – 200 Darbinieki
ApdrošināšanaBūvniecībaNekustamais īpašums
Savvital piedāvā pielāgotus uzņēmējdarbības pakalpojumus maziem un vidējiem uzņēmumiem, kas darbojas starptautiskajos tirgos. Uzņēmuma darbība aptver būvniecību, nekustamo īpašumu, apdrošināšanu, hipotekāros pakalpojumus un vispārēju uzņēmējdarbības atbalstu, uzsverot praktisku uzdevumu deleģēšanu un izmaksu ziņā pārdomātus risinājumus. Apvienojot specializētus pakalpojumus ar uz cilvēku vērstu pieeju, Savvital palīdz klientiem pārvaldīt darbības vajadzības un tiekties uz izaugsmi.
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Vakances uzņēmumā

Supply Chain Forecasting Data Analyst

Turn ERP sales data into demand forecasts and inventory recommendations for Savvital’s customized services to international small and midsize businesses.

GTGvatemalaAttālinātiPilna slodzeVidējais līmenisVecākais speciālistsNepieciešamā Valoda: angļuDatu analītiķis
ERP

Apraksts

  • Find demand patterns and purchasing behavior in historical sales and order data.
  • Forecast demand by SKU and customer.
  • Create rolling 12–18-month forecasts from historical purchasing trends.
  • Compare demand and growth year over year.
  • Annualize year-to-date usage when appropriate.
  • Classify demand as steady, seasonal, sporadic, declining, or growing.
  • Account for units of measure, product categories, and customer purchasing differences.
  • Flag unusual demand shifts, including spikes, drops, and products with no usage.
  • Build scalable forecasting and inventory analysis models in Microsoft Excel.
  • Create Excel formulas, calculations, PivotTables, lookups, and analytical logic for forecasting.
  • Set up recommendations to validate, maintain, or reduce stock levels.
  • Produce exception reports and alerts for products needing review.
  • Test forecasting methods on representative datasets before wider use.
  • Record formulas, assumptions, calculations, and methods.
  • Extract, organize, clean, and validate large datasets from ERP and other business systems.
  • Find inconsistencies, missing information, duplicates, and other data-quality problems.
  • Assess how data issues affect forecasts and analytical results.
  • Set up data-cleaning and validation processes.
  • Share data-quality concerns with relevant stakeholders.
  • Use demand trends to inform inventory and stocking decisions.
  • Identify SKUs that need higher or lower stock levels.
  • Assess how customer purchasing behavior affects inventory needs.
  • Inform inventory planning and replenishment with data analysis.
  • Recommend ways to balance product availability and inventory efficiency.
  • Report historical usage, demand trends, forecasts, and recommendations clearly.
  • Turn complex analysis into practical commercial recommendations.
  • Present findings to non-technical stakeholders.
  • Call out key trends, exceptions, risks, and opportunities.
  • Contribute to customer-facing inventory and demand reports.
  • Work independently and collaborate with business and supply chain stakeholders.
  • Own analytical projects from raw data through final recommendations.
  • Clarify ambiguous requirements or datasets.
  • Explain analytical methods and reasoning clearly.
  • Adjust forecasting methods as business needs or data patterns change.
  • Communicate progress, challenges, and findings effectively.

Prasības

  • Bring at least 3 years of experience in supply chain analytics, demand planning, forecasting, inventory planning, operations analytics, or a closely related analytical field.
  • Have practical experience with demand forecasting and/or supply planning.
  • Demonstrate advanced Microsoft Excel skills.
  • Have strong PivotTable skills.
  • Use XLOOKUP or INDEX-MATCH confidently.
  • Be proficient with SUMIFS and advanced Excel formulas.
  • Have experience cleaning and transforming data.
  • Have experience analyzing trends.
  • Have experience calculating growth rates.
  • Have experience building forecasting models.
  • Have experience working with large datasets.
  • Have experience extracting, cleaning, and analyzing ERP data.
  • Be able to build analytical models from raw transaction data, beyond maintaining existing reports.
  • Understand SKU-level demand and inventory concepts well.
  • Apply strong analytical reasoning and problem-solving skills.
  • Work independently with incomplete, inconsistent, or imperfect data.
  • Communicate effectively in written and spoken English.
  • Explain analytical findings clearly to non-technical stakeholders.

Priekšrocības

  • Premium internet allowance
  • Electricity allowance
  • Wellbeing allowance
  • Annual performance-based pay increases
  • Structured career progression
  • Individual performance-based bonuses
  • Team target bonuses

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