Data Scientist - Data Acquisition

and task allocation. You will be at the center of a cross-functional initiative to improve how data signals are captured, transformed, and used to guide critical assignments within a scaled delivery framework.
This role requires fluency in building data-driven allocation systems, deep comfort with experimentation and analysis, and the ability to translate real-world challenges into technical solutions using machine learning and statistical modeling.

Job Description

1. Optimisation Modelling: Design and develop data-driven models and frameworks that support intelligent assignment, prioritization, and resource utilization across operational workflows.
2. Feature Engineering: Build and maintain pipelines that transform raw signals such as behavioral data, labelling task attributes, and performance metrics into structured features for decision-making.
3. Project Planning and Execution: Develop and manage project plans, timelines, and budgets for data science initiatives.
4. Stakeholder Management: Communicate project progress, challenges, and results to stakeholders and senior management.

Qualifications

Minimum Qualifications

1. At least 5 years of experience applying machine learning, statistical modeling, or optimization to operational or business challenges.
2. Strong skills in data wrangling, feature development, and exploratory analysis.
3. Proficient in Python and SQL; experience working with large-scale or distributed data systems.
4. Track record of owning end-to-end data projects, from requirements gathering to implementation.

Preferred Qualifications

1. Background in decision science, resource allocation models, or workflow optimization.
2. Experience working within structured operational environments such as service delivery, content review, or quality control systems.
3. Understanding of experimentation infrastructure, including A/B testing and metric design.
4. Ability to communicate technical insights clearly to both technical and business audiences.