Data Scientist Intern

Posted:
10/12/2024, 1:35:12 AM

Location(s):
Tyrol, Austria ⋅ Wildschönau, Tyrol, Austria

Experience Level(s):
Internship

Field(s):
AI & Machine Learning ⋅ Data & Analytics

Workplace Type:
Remote

We're looking for a Data Scientist Intern to join our Leidos team!

The position requires general machine learning and artificial intelligence knowledge related to AI-ready data, data governance, creating data repositories, exploratory data analysis, and applying various data schemas based on the analytical use case. The candidate will contribute to multiple machine learning (ML) and artificial intelligence (AI) projects in the Leidos AI/ML Accelerator. Candidates must be familiar with handling numerous data types (text, image, video, audio, lidar, etc..). The candidates must understand how to construct and format data for various AI algorithms. Ethical AI is part of all Leidos AI/ML projects. Consequently, we want candidates to know the concepts of Ethical AI and how to apply them to data construction.

Along with those skills, the candidate must have demonstrated the ability to work independently and in technical teams to implement and customize algorithms to fuse multiple data modalities. In this position at Leidos Arlington, VA. the candidate should have at least intermediate Python coder ability and hands-on experience using ML libraries like SciKit Learn, DKube, KubeFlow, Feast, Azure, TensorFlow, Keras, etc. The candidates' knowledge should also include experience containerizing AI models and using the containers with AWS, Microsoft Azure, or Google Cloud.

Primary Responsibilities

  • Synthetic Data Generation
  • Federated Learning skills
  • Automated Data Labeling
  • Data Marketplace concepts
  • AI-Driven Data Preparation
  • Create AI/ML prototypes for use cases requiring identifying entities/objects, determining object association, object disambiguation, anomaly detection, state estimations, etc.
  • Develop and maintain data models (both physical and logical)
  • accuracy, integrity, and information assurance and security.
  • Conduct anomaly detection using various AI/ML techniques

Basic Qualifications

  • Must be pursuing a degree in a related field of study at an accredited college/university
  • Must be able to obtain a Top-Secret security clearance with a polygraph
  • US citizenship required
  • Knowledge of Deep Learning Frameworks such as Keras, Tensorflow, PyTorch, Mxnet, etc. - Ability to apply these frameworks to real problems in the 'time --series' domain
  • Practical hands-on experience and the ability to explain statistical analysis, reinforcement learning, transfer learning, natural language processing, and computer vision

Preferred Qualifications

  • Visualizations/Web Development Skills (e.g., Tableau, D3, etc.).
  • Hands-on experience with prototype development
  • Hands-on experience with automating data cleansing, formatting, staging, and transforming data human
  • Hands-on experience applying data analytics
  • Hands-on experience with prompt engineering
  • Hands-on experience with reinforcement learning
  • Hands-on experience with LLMs and Generative AI
  • Hands-on experience with intelligent systems and machine learning
  • Experience with interpretability of deep learning models
  • Big Data Skills (Azure, Hadoop, Spark, recent deep learning platforms)
  • Experience with text mining tools and techniques, including in areas of summarization, search (e.g., ELK Stack), entity extraction, a training set generation (e.g., Snorkel), and anomaly detection
  • Hands-on experience with DKube
  • Hands-on experience with KubeFlow
  • Hands-on experience with Feast

Original Posting Date:

2024-10-12

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $53,950.00 - $97,525.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.