Trainee Consultant-Data Science

Careers

Trainee Consultant - Data Science 11032026

Trainee Consultant-Data Science APPLY NOW United States of America Seattle Full Time

About Applexus:

Applexus is a global technology and business consulting firm founded in 2005 and headquartered in Seattle, with delivery centers across North America, Canada, the United Kingdom, and India. We help enterprises realize value from AI and advanced analytics by applying AI/ML solutions directly to core business processes. With strong foundations in SAP and enterprise platforms, Applexus delivers AI-driven transformation across SAP S/4HANA, data modernization, analytics, and cloud-native architectures. Our focus is on translating enterprise data into actionable intelligence that improves decision-making, operational efficiency, and business outcomes. Applexus approaches AI pragmatically designing solutions that are scalable, governed, and ready for real-world enterprise deployment.

Applexus AI Practice

The Applexus AI Practice is built on deep domain expertise and a strong understanding of enterprise systems, particularly SAP. We combine this knowledge with our proprietary AI accelerators to help organizations move from AI exploration to production-ready implementation. Our teams embed intelligent automation into the fabric of enterprise operations, enabling AI systems that operate within existing workflows rather than alongside them. These solutions are designed to integrate seamlessly with SAP landscapes while meeting enterprise standards for security, reliability, and performance.

A key area of focus is Agentic AI-autonomous, goal-driven systems that can reason and act across enterprise processes. By pairing agentic architectures with SAP domain expertise, Applexus delivers AI solutions that are context-aware, governed, and built for scale.

About the Role:

We are looking for a motivated and inquisitive Trainee Consultant - Data Science to join our team. In this role, you will contribute to real-world machine learning and data science projects under the mentorship of experienced professionals. This opportunity is ideal for individuals who are eager to apply their academic knowledge, expand their technical skills, and gain hands-on experience in AI/ML technologies in a collaborative environment.

Skills & Qualifications:

• Master's degree in data science, Artificial Intelligence, or a related field from an accredited U.S. university.
• Proficiency in Python
• Familiarity with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, or Keras
• Solid understanding of statistics, linear algebra, and core machine learning algorithms
• Strong analytical and problem-solving abilities
• Capable of working both independently and collaboratively in a team environment

Key Responsibilities:

• Assist in the design, development, and evaluation of machine learning models
• Perform data cleaning, preprocessing, and feature engineering tasks
• Contribute to projects involving predictive modeling, natural language processing (NLP), or computer vision
• Utilize Python and tools such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch in project execution
• Collaborate with team members to analyze outcomes and generate actionable insights
• Maintain thorough documentation of work, models, and findings

What You'll Gain:

• Practical, hands-on experience with leading AI/ML technologies
• Mentorship and guidance from experienced professionals in the field
• Opportunity to contribute to real-world projects with measurable impact
• Potential consideration for future full-time roles will be based on performance during the training tenure

How to Apply:

Interested candidates may apply through the career site by submitting their full resume. Preference will be given to U.S. Citizens and Green Card holders. Candidates on OPT with STEM extension eligibility are also welcome to apply and will be considered based on merit. If on OPT, please specify the validity period and indicate STEM eligibility.

Location: Seattle, USA Work Hours: Full Time (40 hours per week) Join the Team APPLY NOW