Role overview
About this role
At IBM Research, we are the innovation engine of IBM. Exploring what’s next in computing and shaping the technologies the world will rely on tomorrow. From advancing AI and hybrid cloud to pioneering practical quantum computing, we anticipate challenges and unlock new opportunities for clients, partners, and society. Working in Research means joining a team that accelerates discovery at the intersection of high-performance computing, AI, quantum, and cloud. You’ll collaborate with leading scientists, engineers, and visionaries to push boundaries and turn ideas into reality. With a culture built on curiosity, creativity, and collaboration, IBM Research offers the opportunity to grow your career while contributing to breakthroughs that transform industries and change the world. Within IBM Quantum, the Adoption Team is an elite team serving our partners as they research quantum computing solutions for their most pressing business challenges. We keep our partners up to date with the latest technical advances, and make sure they are empowered to use our software and services. As a data scientist intern, you will be supporting our data and analytics mission to drive reporting on and insights into the IBM Quantum partners and community members and your work will enable the team to make data-driven decisions. Focus areas will include adoption and impact of IBM Quantum hardware, software, learning and outreach content, and events. As a data scientist intern, your key stakeholders will be client/community-facing teams at IBM Quantum. In addition, you will interface across many individuals and parties at partner institutions and within IBM, including technical teams within IBM Quantum, product, marketing, and business development teams. You will support end-to-end workstreams, such as the building of new analytics resources and performing of advanced (predictive) data analysis. Successful attributes to thrive in this role are: Creative in framing and solving complex problems Self-starter Agile in navigating a complex organization and in stakeholder management Organized, with exceptional project management skills Quick learner with an independent growth mindset Able to absorb new technical concepts quickly and thoroughly Excellent communication skills, with the ability to explain technical concepts clearly Enthusiasm about quantum computing and data science. Pursuing a masters or PhD degree in data science or other quantitative field such as mathematics, computer science, statistics or physics. Proficiency with SQL and experience working with relational databases. Proficiency with Python and libraries commonly used for data analysis (e.g., NumPy, Pandas, SciPy, scikit-learn, matplotlib, Seaborn, etc.). Knowledge of common machine learning algorithms and frameworks: linear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience building dashboards with one or more data visualization tools (experience with Metabase and/or Amplitude a plus) Experience with Github or other version control platform(s). Demonstrated ability to communicate project insights and findings and propose actionable next steps.