Data Science Intern Job Listing at Intelsat in Chicago, IL (Job ID 42000)

Description

Position Description: 

The Data Science intern will collaborate with their team and engage with stakeholders from various business functions to implement AI-driven solutions. As a Data Science intern, you will:

• Engage in a variety of artificial intelligence (AI), machine learning (ML), and generative AI (Gen-AI) projects from requirements to POC, prototype, and MVP development.
• Employ various algorithms and ML/DL techniques customized for particular business use cases.
• Collaborate with senior Data Scientists and ML Engineering along the key stages of the AI/ML lifecycle – data acquisition, feature engineering, model development and training, model evaluation and tuning, model deployment and monitoring. 
• Document AI/ML model development processes and methodologies.
• Gain knowledge in the space and satellite industry while increasing exposure working with other business functions to ensure a full understanding of the company structure and strategy.
• Present AI/ML project findings and recommended course of action to leadership and key stakeholders.

Job Responsibilities:

The Data Science intern will have the opportunity to:

• Design, develop and deploy AI-powered solutions to optimize Intelsat's network, increase operational efficiencies, and improve end-user's quality of experience.
• Gain a better understanding on AI/ML solution implementation and model performance monitoring.
• Conduct research on AI trends, technologies, and techniques. Prototype 1 new technology. 
• Collaborate with stakeholders to identify opportunities for AI implementation and optimization.
• Learn from senior staff – business strategy, business processes, AI/ML approaches/techniques, explainable AI, data storytelling, influencing others.

Preferred Qualifications: 

• Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Statistics, or equivalent quantitative discipline with emphasis on AI/ML.
• Familiarity with supervised, unsupervised, reinforcement learning and related ML techniques (regression, classification, clustering) to support model solution development – prediction, optimization, recommendation. Basic knowledge of other AI sub-domains e.g., deep learning (ANN), NLP, Gen-AI / LLMs, a plus.
• Familiarity with ML frameworks and libraries (PyCaret, Scikit-learn, PyTorch,  Tensorflow/Keras, NumPy, Pandas) and range of functions and algorithms they provide to train/test models. 
• Experience in programming, analytical, and visualization tools to extract, transform, summarize, and visualize data that aligns with the objectives of an AI or data science project:
  • Python (intermediate)
  • SQL (intermediate)
  • MS Excel (intermediate)
  • Tableau, PowerBI (familiar)
  • Jupyter or other Python-based data viz libraries (familiar)
• Experience utilizing relational databases and data lakes working with a variety of data structures, formats, and types.      Use of cloud-based platforms i.e., AWS, Snowflake, Azure, GCP, a plus.
• Analytical thinking, collaborative mindset, strong communication, and time management skills

12 Week Schedule: 

• Week 1-3: Business Foundation and Data Understanding
  • On-boarding and training
  • Data discovery, acquisition, exploratory data analysis (EDA)
  • Data pre-processing, feature engineering
• Week 4-6: Model Design and Development
  • Research algorithms and ML techniques that match use case
  • Implement baseline models
  • Train models, fine-tune hyperparameters
  • Evaluate model performance; conduct cross-validation
• Week 7-10: Advanced Modeling and Analysis
  • Analyze feature importance and iterate feature selection
  • Refine models, consider alternatives, compare vs. baseline
  • Optimize model performance
  • Create documentation (architecture, features, performance)
• Week 10-12: Deployment, Monitoring, and Reporting
  • Collaborate with ML Engineering / CloudOps on deployment environment
  • Deploy model into production, monitor performance
  • Finalize comprehensive report of the project
  • Present findings to stakeholders

Minimum Requirements:

• Eligible candidates must be one of the following:
  • Part-time or full-time students who have completed 24+ credit hours (rising sophomores/juniors/seniors) and are enrolled in an undergraduate program at an accredited college or university; Part-time or full-time students enrolled in a graduate program at an accredited college or university.
  • May 2025 graduate 
• Ability to exercise sound judgment, professionalism, and maturity in the workplace
• Effective communicator in both written and spoken English
• Good oral and written communication skills
• Proficiency in use of MSOffice Suite
• 3.0 GPA or above preferred

Summer Intern Program Description:

• Paid; 12 weeks starting on Monday, May 26, 2025, through August 15, 2025
• Schedule - 40 hours/week, Monday- Friday, 9 – 5 or regular core hours
• Hybrid environment (minimum 3 days in Chicago location)