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About this opportunity:

Sales and Operations Planning (S&OP) aligns demand, supply, inventory, production capacity, service levels, and financial objectives across mid- to long-term horizons. Yet manual spreadsheets, fragmented data, and static plans often leave planners focused on reconciliation rather than timely, cross-functional decisions.

This thesis explores how an AI-driven platform can automate data integration, detect demand and supply changes, simulate adjusted production plans, and recommend prioritized actions. By quantifying operational and financial trade-offs—including delivery, inventory, capacity, costs, revenue, margins, and cash flow—the platform would support, not replace, planners. Its value should be measured through reduced planning time and manual workload, improved inventory and delivery performance, lower supply-chain costs, and faster, more transparent responses to disruptions.

What you will do:

You will develop a conceptual, practically applicable AI platform for automated S&OP scenario planning that responds to demand and supply changes, focusing on:

• Platform architecture and data integration: Design near-real-time integration of sales, forecasts, supply, inventory, production, capacity, and financial data, including data models, pipelines, master-data governance, and enterprise-system integration

• Scenario simulation and adaptive planning: Detect and model demand and supply changes, from forecast revisions and order fluctuations to shortages and downtime, then automatically generate, simulate, and evaluate adjusted production plans

• Recommendations and decision support: Generate and rank actions across capacity, inventory, sourcing, production scheduling, demand allocation, and delivery trade-offs using multi-criteria optimization, reinforcement learning, or rule-based logic

• Segmentation and planning horizons: Adapt capabilities by strategic, tactical, or operational horizon, product lifecycle, supply-chain tier, and product-location or product-plant combination, balancing standardized automation with analyst-led planning for volatile or constrained segments

Research may combine literature review, historical operational and financial data analysis, and stakeholder interviews or workshops. Methods may include architecture and data engineering, anomaly detection, forecasting, discrete-event and Monte Carlo simulation, mixed-integer and multi-criteria optimization, reinforcement learning, and cost-benefit analysis. The final framework should guide where to automate, standardize, differentiate, simplify, or transform S&OP through AI.

The skills you bring:

• Suitable background: Supply Chain Management, Industrial Engineering, Operations Research, Data Science, Business Analytics, Computer Science, Economics, or similar

• Knowledge of S&OP, demand planning, production planning and control, inventory management, forecasting, optimization, simulation, machine learning, data engineering, and system design is a plus

• Familiarity with data science modeling techniques—including predictive and statistical modeling, time-series analysis, feature engineering, exploratory data analysis, causal inference, and clustering and classification—and proficiency in data analysis tools and languages such as Python, R, and SQL is advantageous

Why join Ericsson?

At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.

What happens once you apply?

Click Here to find all you need to know about what our typical hiring process looks like.

Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.

Primary country and city: Sweden (SE) || Stockholm

Req ID: 793186