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Armonk, NY

Internship

Hybrid

$101K/yr - $185K/yr

Intern

IBM is hiring a Data Scientist Intern to help implement AI- and data-driven solutions aligned with business goals. The intern will develop and deploy models, translate business needs into technical strategies, and communicate insights to stakeholders.

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Responsibilities

Support the design, implementation and optimization of AI-driven strategies per business stakeholder requirements
Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights
Apply GenAI, traditional AI, ML, NLP, computer vision, or predictive analytics where applicable
Collect, clean, and preprocess structured and unstructured datasets
Help refine data-driven methodologies for transformation projects
Learn and utilize cloud platforms to ensure the scalability of AI solutions
Leverage reusable assets and apply IBM standards for data science and development
Apply ML Ops and AI ethics
Translate business requirements into technical strategies
Ensure alignment to stakeholders’ strategic direction and tactical needs
Apply business acumen to analyze business problems and develop solutions
Collaborate with stakeholders and team to prioritize work
Manage and contribute to various stages of AI and data science projects, from data exploration to model development to solution implementation and deployment
Use agile strategies to manage and execute work
Monitor project timelines and help resolve technical challenges
Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs
Communicate regularly and present findings to collaborators and stakeholders, including technical and non-technical audiences
Create compelling data visualizations and dashboards
Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems

Qualification

Required

High School Diploma/GED
Pursuing a Bachelor's degree in Computer Science, Data Science, Statistics, Economics, or a related field
Experience with AI/ML technologies and statistical modeling through coursework, projects, or past internships or full time positions
Proficiency in SQL and Python for performing data analysis and developing machine learning models
Experience and/or coursework in statistics, machine learning, generative and traditional AI
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
Familiarity with cloud-based platforms and data processing frameworks
Understanding of large language models (LLMs)
Familiarity with object-oriented programming
Experience and/or coursework with common Python libraries used by data scientists (e.g., NumPy, Pandas, SciPy, scikit-learn, matplotlib, Seaborn, etc.)
Strategic thinking and business acumen
Strong problem-solving abilities and eagerness to learn
Ability to work with datasets and derive insights
Attention to detail
Excellent communication skills, with the ability to explain technical concepts clearly
Independent and team-oriented
Understands AI Ethics principles
you must have the ability to work without a need for current or future visa sponsorship

Preferred

Bachelor's Degree

Benefits

Up to 8 paid holidays for eligible Supplemental 1 employees.
A minimum of 56 hours of paid sick time for eligible Supplemental 1 employees.
IBM Employee Stock Purchase Plan for eligible Supplemental 1 employees.
Paid family medical leave and disability benefits to eligible employees where required by applicable law.
Hybrid work arrangement.
Opportunities to enhance programming skills, critical thinking, and problem-solving abilities.
Networking opportunities within IBM's global business and technology ecosystem.
Opportunities to learn and develop your skills and career, with ongoing feedback and support.

IBM provides technology and consulting, including software, infrastructure systems, and cloud-based solutions.

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