Senior Data Scientist at SGS

Madrid, Madrid Community, Spain -

Full Time

Start Date

Immediate

Expiry Date

29 Jan, 26

Salary

0.0

Posted On

01 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, AI, Python, NLP, Computer Vision, Generative AI, MLOps, DevOps, Project Management, Analytics, Collaboration, Communication, Statistical Knowledge, Leadership

Industry

Professional Services

Description

Company Description At SGS, we are the world's leading testing, inspection, and certification company, setting the global benchmark for sustainability, quality, and integrity. With a network of 2,650 offices and laboratories and a dedicated team of 97.000 employees, we work together to create a better, safer, and more interconnected world. Job Description Our Digital Builders Organization is an internal team supporting the entire SGS business. Its objective is to drive new IT solutions based on SGS Business Units needs and requests, allowing the company to optimize its processes, improve its results and generate value for its clients.These IT solutions are developed through a key work methodology based on an agile approach, hybrid teams and short time to market. As a Data Scientist, you must be able to convert in reality the business requirements related to our digital transformation where cloud technology is a key enabler. You will be working in the implementation of data MVPs as part of a Digital Builders Organization squad. More Specifically, You Will Collaborate with Business Units to have a deep understanding of the business problem that AI and Machine Learning may solve. Provide technical expertise in the use cases execution, collaborating with IT to achieve optimal solutions. Support the Product Owner in defining the scope and measurable metrics to evaluate the results of the solution to be built. Work with architects to move from the scope of the MVP to the final picture in terms of data. Take ownership of the AI/ML and data components in the MVPs implementation to develop rapid data solutions that address user needs. Work closely with data owners to leverage data to build products. Ownership of the projects you will be involved. Promote internally and externally the work performed by the DBO Data Team to facilitate discovery of new use cases where to apply AI/ML technologies. Qualifications + 6 years of professional experience in developing AI/ML solutions; experience applied to business problems; Educated to degree level in Analytics, Business Intelligence, Data Science, Economics, Engineering or Statistics, or equivalent experience in a professional setting. Python programming with focus on Machine Learning applied to prediction, NLP, Computer Vision and/ or Generative AI (must). Other programming languages and platforms will be valued; MLOps/ DevOps; Statistical knowledge is a plus; Demonstrated aptitude for analytics; Project management skills or certifications (Scrum Master, PMI, Lean) is a plus; Proven record of leadership in a work setting and/or through extracurricular activities; Ability to work collaboratively in a team environment; Ability to work effectively with people at all levels in an organization; Skills to communicate complex ideas effectively; Ability to communicate complex ideas effectively – both verbally and in writing – in English and the local office language(s) Additional Information Why SGS? Global and very stable company, world leader in the TIC (Testing, Inspection and Certification) industry. Flexible schedule and hybrid/remote work model. SGS university and Campus for continuous learning options. Multinational environment where you will work with colleagues from multiple continents. Benefits platform. Join Us: At SGS, we are committed to fostering an open, friendly, and supportive culture that thrives on teamwork. We value diversity and provide endless opportunities to learn, grow your expertise, and fulfill your potential. Apply now to be part of our motivated and dynamic team!

Responsibilities

Collaborate with Business Units to understand business problems that AI and Machine Learning can solve. Take ownership of AI/ML and data components in MVPs implementation to develop rapid data solutions.