Supply Chain Forecasting & Data Analyst

Savvital is seeking a highly analytical Supply Chain Forecasting & Data Analyst to support its expanding supply chain and distribution operations. This role involves transforming historical sales and order data into accurate demand forecasts, inventory insights, and actionable business recommendations. The ideal candidate will work hands-on with large transactional datasets, cleaning and validating data, identifying demand patterns, building forecasting models, and analyzing SKU and customer behavior. This position requires someone who can independently develop reliable models from raw data and communicate findings clearly to business stakeholders.

Key Responsibilities

- Analyze historical sales and order data to identify demand patterns, purchasing behavior, and growth trends at SKU and customer levels.
- Develop rolling 12 to 18-month demand forecasts, accounting for seasonal, sporadic, declining, and growing demand patterns.
- Build scalable forecasting and inventory analysis models using advanced Microsoft Excel functions such as PivotTables, XLOOKUP, SUMIFS, and complex formulas.
- Create recommendation logic to guide stocking decisions, including increasing, maintaining, or reducing inventory levels.
- Extract, clean, and validate large datasets from ERP and other business systems, addressing inconsistencies, duplicates, and missing information.
- Identify unusual demand changes like spikes or drops and communicate data-quality concerns effectively to stakeholders.
- Provide inventory and supply chain insights to support replenishment decisions, balancing product availability with inventory efficiency.
- Prepare clear, concise reports translating complex analyses into practical recommendations for non-technical audiences.
- Collaborate with supply chain and business teams, taking ownership of projects from raw data through to final recommendations.
- Adapt forecasting methodologies based on changing business requirements or data patterns, and communicate progress and challenges transparently.

Required Qualifications

- Minimum of 3 years’ experience in supply chain analytics, demand planning, forecasting, inventory planning, or related analytical roles.
- Proven hands-on experience with demand forecasting and supply planning.
- Advanced proficiency in Microsoft Excel, including building complex models and data transformation.
- Strong skills in data cleaning, trend analysis, growth-rate calculations, and working with large datasets.
- Experience extracting and analyzing data from ERP systems.
- Ability to independently build analytical models from raw transactional data rather than maintaining existing reports.
- Solid understanding of SKU-level demand and inventory management concepts.
- Excellent analytical reasoning, problem-solving skills, and attention to detail.
- Strong written and verbal communication skills, capable of explaining complex analysis to non-technical stakeholders.
- Comfortable working independently with incomplete or imperfect data.

Preferred Qualifications and Benefits

Experience with Microsoft Dynamics 365 Business Central, Power BI, inventory optimization, demand and supply planning, Sales & Operations Planning (S&OP), manufacturing, wholesale or distribution, and industrial supply chains is advantageous. Familiarity with customer-level forecasting, inventory replenishment models, exception reporting, and customer-facing inventory or demand reports is also beneficial.

Compensation includes a market-competitive base salary based on experience, premium allowances for internet, electricity, and wellbeing, comprehensive medical insurance, annual performance-based increments, structured career progression, and individual and team-based bonuses.

Savvital values its employees and fosters a culture that emphasizes the unique contributions and experiences each individual brings to the organization. The company encourages candidates who have personally built forecasting models and worked extensively with ERP datasets to apply, highlighting real examples of their analytical work and outcomes.