Python Developer

Job Title: Python Developer

Location: Dike Street, 8 - 2630 Aartselaar, Belgium

Work mode: Hybrid

Language: Dutch

Duration: 01/01/2025- 31/12/2025

Description of the Roles:

As an Analyst - Programmer, you are responsible for setting up an edge algorithm for smart control of nitrogen removal (aeration). The tasks are split into two separate roles given the difference in required knowledge and competencies.

This algorithm is developed based on an approach/example provided by the Client. This requires a specialized academic profile with relevant experience and knowledge of concrete applications in industrial production processes.

• As an Analyst:
• You map out the needs.
• Make the functional translation of those needs into a functional specification (technical model), develop it into code (Python), and test the algorithm/real-time control E2E.
• There is a need for a structured approach, good analysis documentation, and a lot of communication with the parties involved. You participate in scrum meetings to follow up on the status, problems, guide, define necessary actions, etc.
• This algorithm/smart control is complex in nature. On the one hand, it concerns the necessary data flows, data needs, machine learning & AI, cost aspects of calculation and storage, edge application, etc. But also the necessary insight into error messages from smart controls, alarms towards operations, as well as general and functional follow-up.
• The following aspects, among others, are well mapped out during the design and should be carefully considered in the general architecture, the design of the algorithm, the design of the data flows, etc.:
• Overall strong focus on cost, simplicity, and maximization of practical applicability.
• Reliability: analysis of potential points of failure.
• The system must work automatically in both hardware and software without increased risks and without manual intervention. There is an automatic (own) check for reliability -> fallback strategy.
• Runs within Client network, no shielded code, code fully visible and editable, no non-Client IP.
• Minimization of cost and simplicity vs. minimum required complexity (KISS):
• Trade-off accuracy and cost/speed.
• Frequency calculation/data transfer, volumes, etc.
• Cost of data transfer, bandwidth, data storage, computing time/cost, energy consumption calculations, etc.
• Required speed and acceptable latency (Edge).
• State of the art vs. state of the need, etc.
• Scalability.
• Calibrability: Focus on the robustness and simplicity of the automatic calibration (several days' worth of data).
• Flexible and future-proof (in view of new insights, other models, or changes to models in the future, etc.).
• Attention to the necessary data "pre-processing" to compensate/ignore the influence of "noise," measurement errors, bias, drift, missing data, outliers, etc.

Concrete Knowledge & Capabilities:

• Specialized academic knowledge and relevant experience in the application of modeling/MPC in industrial production processes.
• Analytical thinking: Analyze and solve complex problems through logical thinking and reasoning.
• Analytical depth: Experience with in-depth analysis is required; the data within the Client can be complex and widely spread in systems, databases, and even manual data, being able to see the wood for the trees is important.
• Linking business processes to systems, data, and ultimately to processes and the functional building blocks behind smart control.
• Experience with data integration: Integrating data from different sources and systems to arrive at a usable result in the context of management.
• Good communication skills: Explain technical information understandably to non-technical stakeholders, think along and empathize with the various business areas and digital departments to bring the final solution to a successful conclusion in terms of business needs and all stakeholders.
• Provide handover at the end of a use case to OT and operations.
• Knowledge of relevant laws and regulations: Awareness of privacy, security, and data safety laws and regulations.
• Knowledge of Agile (SAFE) operations, sprint operations, and possibly SCRUM master experience is a serious plus.
• Knowledge of Azure, Machine learning & AI, Databricks, MQTT/ActiveMQ, PLC operation, is a plus.
• Advanced knowledge of Python is required.
• Experience in different aspects of data analysis: data source analysis, process analysis, data modeling, data reporting, data architecture, data quality, master data management, etc.
• Testing: Experience in developing and executing test scenarios.