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Senior Data Scientist

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!

Average salary estimate

$100000 / YEARLY (est.)
min
max
$80000K
$120000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Scientist, SGS

At SGS, the world’s leading testing, inspection, and certification company, we are on the lookout for a talented Senior Data Scientist to join our dynamic Digital Builders Organization team based in Barajas, Madrid. In this role, you’ll play a crucial part in transforming business needs into actual IT solutions that drive our digital evolution forward. You'll collaborate closely with various Business Units to provide insights into how AI and Machine Learning could provide effective solutions to their challenges. Not only will you have the opportunity to implement data MVPs, but you will also define the project scope alongside the Product Owner and support the data architecture of the projects you own. With an agile working methodology and a strong focus on collaboration, your expertise will help optimize processes and generate significant value for our clients. Your experience in developing AI/ML solutions and proficiency in programming with Python will be essential as you work on exciting projects that leverage cloud technologies. Plus, you'll enjoy a flexible working schedule and the chance to be a part of a supportive team culture that thrives on innovation and growth. If you're ready to make an impact and contribute to our mission of creating a safer, more interconnected world, we invite you to embark on this journey with us at SGS!

Frequently Asked Questions (FAQs) for Senior Data Scientist Role at SGS
What are the key responsibilities of a Senior Data Scientist at SGS?

As a Senior Data Scientist at SGS, your primary responsibilities include collaborating with various Business Units to understand their challenges, providing technical expertise for AI and Machine Learning use cases, supporting the Product Owner in defining project scope and metrics, and actively participating in the development of data MVPs. You'll also take ownership of AI/ML components in project implementations and promote the innovative work of the DBO Data Team.

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What qualifications are required for the Senior Data Scientist position at SGS?

To qualify for the Senior Data Scientist role at SGS, candidates should have over 6 years of professional experience in AI/ML development, ideally applied to real-world business problems. A degree in Analytics, Data Science, Engineering, or a related field is essential. Proficiency in Python, especially for Machine Learning applications, is a must, while experience with MLOps, statistical analysis, and project management standards are valued.

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How does the Digital Builders Organization at SGS operate?

The Digital Builders Organization at SGS operates using an agile methodology, focusing on short time-to-market for IT solutions that cater to the needs of various business units. This collaborative team employs hybrid working models, ensuring seamless communication and teamwork to implement effective digital solutions that optimize processes and enhance client value.

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What skills are beneficial for a Senior Data Scientist at SGS?

In addition to technical expertise in AI and Machine Learning, a Senior Data Scientist at SGS should possess strong analytical skills, project management experience, excellent communication abilities, and a demonstrated capacity for teamwork. The ability to collaborate effectively with diverse teams and articulate complex ideas clearly is crucial in this role.

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What is the work culture like at SGS for a Senior Data Scientist?

The work culture at SGS for a Senior Data Scientist is open, friendly, and highly supportive. The company encourages teamwork and values diversity, offering numerous opportunities for continuous learning and professional growth within a multinational environment. Employees enjoy a flexible work culture that fosters collaboration, innovation, and respect, making it a great place to advance your career.

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Common Interview Questions for Senior Data Scientist
Can you describe your experience with developing AI/ML solutions relevant to business problems?

In your response, highlight specific projects where you've applied AI/ML to solve business challenges, detailing your role and the impact of your work. Be sure to mention the tools and techniques you used and how they contributed to the strategic goals of the organization.

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How do you handle data exploration and feature selection in your projects?

Discuss your approach to data exploration, including the techniques you use to analyze data distributions and relationships. Highlight your methods for selecting relevant features, such as statistical tests or feature importance rankings, and how these choices impact model performance.

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What programming languages are you proficient in, and how have you applied them in your data science projects?

Mention your proficiency in Python and any additional languages you are skilled in. Provide examples of how you've utilized these languages for data analysis, machine learning model development, or automation of processes, illustrating your hands-on experience.

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Can you give an example of a particularly challenging data project you've worked on?

Describe a complex project, detailing the challenges you faced and how you overcame them. Focus on the methods you used, teamwork involved, and the final outcomes, emphasizing any innovation or unique solutions you implemented.

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Explain your understanding of MLOps and its relevance to the data science process.

Outline what MLOps means to you, focusing on its importance in bridging the gap between model development and deployment. Discuss the practices you follow for monitoring, maintaining, and retraining models post-deployment to ensure long-term effectiveness.

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How do you ensure effective communication of complex ideas to non-technical stakeholders?

Share strategies you use to simplify complex concepts, such as using visual aids or analogies. Discuss your approach to tailoring your presentations to the audience’s level of understanding and how you prioritize key messages.

Join Rise to see the full answer
What steps do you take to validate a machine learning model?

Talk about the validation techniques you employ, such as cross-validation and A/B testing. Highlight your methods for assessing model performance and any metrics you prioritize, ensuring your models provide reliable results.

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What project management methodologies are you familiar with?

Discuss your experience with methodologies like Agile, Scrum, or Lean. Provide examples of how you've applied these frameworks in your projects, illustrating effective project planning, execution, and team collaboration.

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Describe a time when you had to pivot during a data project. How did you handle it?

Share a specific instance where project requirements or conditions changed unexpectedly. Explain your approach to addressing the new challenges, how you communicated with your team, and the adjustments you made to achieve project goals.

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What trends in AI/ML are you most excited about and how would they impact your work at SGS?

Reflect on current AI/ML advancements that intrigue you, such as advancements in natural language processing or generative AI. Discuss how these trends can be leveraged in your projects at SGS to enhance outcomes and drive innovation in the company's practices.

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SGS is an inspection, verification, testing, and certification company. The company inspects agricultural products, minerals, petroleum and petrochemicals, motor vehicles, and consumer goods. SGS is headquartered in Geneva, Switzerland.

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Full-time, hybrid
DATE POSTED
April 17, 2025

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