Federal Data Engineer Co-Op

Introduction
A career in IBM Consulting is rooted in long-term relationships and close collaboration with clients across the globe.

You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio, including Software and Red Hat.

Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. You will be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in groundbreaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.

Your Role and Responsibilities

During your co-op, you can enhance your knowledge and gain professional experience by working on client projects. This role provides an exceptional opportunity to build a compelling portfolio, acquire new skills, gain insights into industry, and embrace novel challenges for your future career.

At IBM, we prioritize continuous learning, skill development, and personal growth within a culture of coaching and mentorship. As an intern, you'll experience this culture and have the opportunity to advance to our associate program based on results and performance.

Work experiences you could be exposed to:

• Mentored Analytical Support: Receive mentorship from diverse professionals in science engineering and consulting applying analytical rigor and statistical methods to predict behaviors.
• Generative Artificial Intelligence (AI): Work alongside experienced practitioners to implement generative AI models and algorithms for various applications such as conversational computing, natural language processing, and audio processing. Work with large datasets to train and evaluate generative models, and optimize their performance using various techniques.
• Data Integrations: Develop skills in writing efficient and reusable programs to cleanse integrate and model data. Evaluate model results contributing to data-driven insights.
• Tech-Driven Data Transformer: Utilize program languages like Python to build data pipelines, extracting and transforming data from repositories to consumers. Gain exposure to cloud platforms, ETL tools, and data integration, expanding your tech toolkit.
• Effective Communication: Assist in conveying analytical results to both technical and non-technical audiences, refining your ability to communicate complex findings.

Required Technical and Professional Expertise

• Currently enrolled and pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering, or a related field with an anticipated graduation date of May 2025 or later.
• Strong interpersonal skills that enhance collaboration and relationship building, while also managing dynamic workloads in an agile environment.
• Have initiative and passion to actively seek new knowledge and improve skills while embracing a growth mindset to assimilate diverse viewpoints.
• Demonstrate leadership experience and ability to communicate effectively through active listening; while also be willing to adapt and have a readiness to take ownership of tasks and challenges.
• Familiarity with one or more scripting languages (Python preferred), or a proven computer science foundation.
• Ability to work in-office on-site in Reston, VA
• Ability to work up to 20 hours per week
• Ability to obtain and maintain a Federal security clearance while in IBM Consulting

Preferred Technical and Professional Expertise

• Demonstrate familiarity or interest in statistical analysis or data mining through previous internships, personal/academic projects, hackathons, and/or publications
• General familiarity with databases, data-engineering tools (SQL, spark) and cloud platforms (e.g., IBM Cloud, Azure, AWS). Experience with NLP/LLM/GenAI is a plus
• Experience using machine-learning/data science libraries in python (scikit-learn, SciPy, pandas, PyTorch) is a plus