Sr. Data Scientist / ML Engineer Pricing Model - 20605
Veritaz AB · Stockholm · 6 månader – upp till 12 månader · Deadline 2026-12-03
Veritaz AB is seeking a **Sr. Data Scientist / ML Engineer** for a consulting assignment with a client focusing on data-driven pricing. The client has developed an early-stage machine learning model that generates price recommendations during quotations, and the consultant will step in to take ownership, understand its behavior, and establish sustainable long-term management. Core responsibilities combine **hands-on predictive modeling** and model validation with technical advisory tasks, such as reviewing model architecture and statistical logic, evaluating operational readiness, and transferring knowledge to enable the client’s internal team to independently maintain and develop the solution. The engagement requires a senior professional with solid experience developing machine learning solutions and working with predictive models deployed in **production environments**. Candidates must have practical expertise in model evaluation and model lifecycle management, along with strong statistical analysis skills. The ability to communicate complex statistical relationships and technical concepts clearly to both technical and non-technical business stakeholders is essential.
Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry.
Job Overview
Role Summary
Our client is seeking a senior Data Scientist / ML Engineer for a consulting assignment focused on data-driven pricing. The organization has recently developed a machine learning-based pricing model that generates price recommendations during the quotation process. The solution is currently at an early stage, and the next objective is to take ownership of the model, understand its behavior, and establish a sustainable approach to its long-term management and continued development.
The consultant will play a central role in reviewing the existing solution, evaluating how the model is structured and operates, and enabling the organization to independently understand, use, maintain, and enhance it. The assignment combines hands-on model work with technical advisory responsibilities and internal knowledge transfer.
Key Responsibilities
- Gain a thorough understanding of the existing machine learning-based pricing model and its role in generating quotation price recommendations.
- Review and assess the model's architecture, statistical foundations, behavior, and current implementation.
- Evaluate the model's operational readiness and identify improvements needed for sustainable long-term ownership and maintenance.
- Support the organization in taking over responsibility for the model and establishing appropriate management and development practices.
- Work hands-on with the predictive model to understand, validate, and improve its functionality.
- Explain technical, statistical, and model-related concepts to business stakeholders and other relevant audiences.
- Provide expert guidance on how the model can be used and further developed.
- Contribute to building internal competence in data science, machine learning, and predictive modeling.
Technical Stack & Requirements
- Machine Learning: Strong experience developing and working with machine learning solutions.
- Predictive Modeling: Experience with predictive models that have been deployed into production environments.
- Model Evaluation: Ability to review model construction, statistical logic, behavior, and practical performance.
- Model Lifecycle Management: Experience establishing maintainable processes for model ownership, operation, and continued development.
- Statistical Analysis: Ability to interpret and communicate statistical relationships to both technical and non-technical stakeholders.
Qualifications & Experience
The assignment requires a senior Data Scientist or ML Engineer with practical experience in machine learning and production-deployed predictive models. The successful consultant should be capable of independently analyzing an existing solution, combining technical implementation work with strategic advice, and transferring knowledge to internal teams. Experience communicating complex technical and statistical concepts to varied stakeholder groups is important.