Senior Data Scientist (Based in Spain - Remote)
The Senior Data Scientist position at Auctane is based in Spain and offers a remote work arrangement. Auctane is a company specializing in shipping and logistics solutions, serving e-commerce businesses worldwide. The data science team plays a central role in advancing the company’s data-driven initiatives by leveraging advanced analytics and machine learning to optimize shipping processes and improve customer experience.
In this role, you will be responsible for researching, developing, and deploying data models to support a variety of business objectives. Your day-to-day work will include designing experiments, performing data analysis, building predictive models, and collaborating closely with cross-functional teams such as engineering, product, and operations to translate insights into tangible solutions. You will also contribute to enhancing the overall data infrastructure and pipeline reliability.
To qualify, you should have extensive experience in a similar data science role, with proficiency in Python, SQL, and common machine learning frameworks. A strong background in statistics, mathematics, or a related quantitative field is required, along with proven experience deploying models in production environments. Excellent problem-solving skills and the ability to communicate complex technical findings to non-technical stakeholders are essential.
Auctane offers a competitive compensation package, including a comprehensive suite of benefits. Employees benefit from flexible remote work, generous paid time off, and professional development opportunities. The company prioritizes employee well-being with health insurance options and programs to support work-life balance.
Auctane fosters a collaborative and innovative environment where data-driven professionals have the opportunity to make a significant impact on the global e-commerce sector. Team members have room to grow their skill set and advance in their careers, making it a strong choice for those passionate about leveraging data to solve real-world logistics problems.