Senior Applied Data Scientist 17924
Veritaz ABPublicerad: 2026-05-28
Ansök senast: 2026-06-27
Beskrivning
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.
Assignment Description
We are currently looking for an experienced Senior Data Scientist
What You Will Work On
Develop and maintain predictive models for usage, residual value, lifecycle forecasting, and portfolio risk
Build analytics solutions supporting electric vehicle asset management and pricing strategies
Translate operational and business datasets into actionable recommendations and insights
Define, validate, and document model assumptions, uncertainty, and analytical limitations
Develop simulations, dashboards, APIs, prototypes, and decision-support applications
Collaborate with data engineering teams to ensure reliable data pipelines and data quality
Productionize analytical models using APIs, scheduled jobs, cloud services, testing, monitoring, and versioning
Support finance, sales, product, customer, and partner discussions through data-driven analysis
Structure and drive work forward in unclear or evolving analytical problem spaces
Balance model quality, implementation speed, scalability, and business usability
Contribute to maintainable, trustworthy, and production-ready analytical services
Communicate complex analytical concepts clearly to both technical and non-technical stakeholders
What You Bring
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Engineering, Economics, or related field
Strong Python expertise for analytics, modeling, testing, and production-quality development
Strong SQL skills and experience working with analytical data platforms
Experience building analytical models and tools supporting business-critical decisions
Ability to own work from business problem definition through implementation and stakeholder adoption
Experience deploying or operating cloud-based analytical products, APIs, or model services
Ability to work effectively with incomplete or imperfect data while making sound analytical judgments
Strong engineering mindset with the ability to transform analysis into practical tools and services
Strong communication skills across technical and business-oriented stakeholders
Ability to independently structure and drive analytical initiatives
Pragmatic and analytical mindset with strong self-leadership capabilities
Comfortable working in small teams with broad responsibilities
Assignment Description
We are currently looking for an experienced Senior Data Scientist
What You Will Work On
Develop and maintain predictive models for usage, residual value, lifecycle forecasting, and portfolio risk
Build analytics solutions supporting electric vehicle asset management and pricing strategies
Translate operational and business datasets into actionable recommendations and insights
Define, validate, and document model assumptions, uncertainty, and analytical limitations
Develop simulations, dashboards, APIs, prototypes, and decision-support applications
Collaborate with data engineering teams to ensure reliable data pipelines and data quality
Productionize analytical models using APIs, scheduled jobs, cloud services, testing, monitoring, and versioning
Support finance, sales, product, customer, and partner discussions through data-driven analysis
Structure and drive work forward in unclear or evolving analytical problem spaces
Balance model quality, implementation speed, scalability, and business usability
Contribute to maintainable, trustworthy, and production-ready analytical services
Communicate complex analytical concepts clearly to both technical and non-technical stakeholders
What You Bring
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Engineering, Economics, or related field
Strong Python expertise for analytics, modeling, testing, and production-quality development
Strong SQL skills and experience working with analytical data platforms
Experience building analytical models and tools supporting business-critical decisions
Ability to own work from business problem definition through implementation and stakeholder adoption
Experience deploying or operating cloud-based analytical products, APIs, or model services
Ability to work effectively with incomplete or imperfect data while making sound analytical judgments
Strong engineering mindset with the ability to transform analysis into practical tools and services
Strong communication skills across technical and business-oriented stakeholders
Ability to independently structure and drive analytical initiatives
Pragmatic and analytical mindset with strong self-leadership capabilities
Comfortable working in small teams with broad responsibilities
