Map Operations Specialist(IoT devices/Automation/AI/ML )

About the Assignment:

This assignment aims to onboard a skilled professional to support and optimize map-related operations, with a strong focus on IoT expansion and deployment. The role is pivotal in driving innovation, improving data workflows, and addressing technical challenges in mapping projects, particularly for large-scale initiatives like the KartaDashCam & FoodLocker scale-up.

The Core Objectives:

Design and implement data pipelines to process and analyze large-scale spatial and non-spatial datasets.

Lead the deployment and operation of IoT devices, including supporting large-scale expansion projects (e.g., KartaDashCam, FoodLocker), and perform essential onsite troubleshooting.

Develop solutions to automate map operations and improve data accuracy.

Collaborate with cross-functional teams to integrate technologies and creative ideas into map-related workflows.

Essential Experience / Criteria:

Minimum 2 years of experience in a related field. Fresh graduates with relevant experience and skills are encouraged to apply.

Strong practical knowledge of IoT devices and environments, with hands-on experience supporting large-scale deployments and onsite troubleshooting.

Proficiency in programming languages such as Python and SQL, with hands-on experience in automating data pipelines using tools like Airflow, Spark, or similar.

Strong knowledge of AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and familiarity with cloud-based data platforms (e.g., AWS, GCP, or Azure).

Experience in data visualization using tools like Tableau, Power BI, or similar platforms.Excellent communication and collaboration skills, with the ability to confidently voice ideas and contribute to team discussions.

Ability to work independently or with minimal supervision, while managing tasks effectively.

Regular travel is expected to support fieldwork, site inspections, and IoT deployment activities.

Possesses own transportation.

Desirable Experience / Criteria:

Familiarity with GIS tools (e.g., QGIS, ArcGIS) and geospatial libraries (e.g., GeoPandas, GDAL, Shapely).

Experience working with spatial databases (e.g., PostGIS) or geospatial data platforms.

Proven ability to experiment independently, think creatively, and develop innovative solutions tailored to operational needs.