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Remote Data Science Intern Jobs in Alabama (NOW HIRING)

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field. * Active Secret clearance preferred; ability to obtain one is required . #LI-KM1 #LI-Remote ...

A bachelor's degree in computer science or related field or commensurate, documented experience in ... Turning complex operational data into actionable intelligence, Octave connects expertise, real ...

Configure and manage map services and data publishing workflows to ensure timely and accurate data ... Bachelor's degree in Geographic Information Systems, Computer Science, Geography, or a related ...

Configure and manage map services and data publishing workflows to ensure timely and accurate data ... Bachelor's degree in Geographic Information Systems, Computer Science, Geography, or a related ...

Lead simple data modeling and data conversion definition activities * Performs complex ... A degree in the Sciences, Computer Sciences, Engineering or a related discipline, or equivalent ...

Implement formal modeling processes from end to end including data gathering, data profiling ... BA/BS in statistics, mathematics, actuarial science or related area and 5 years of post-bachelor ...

Perform complex data analysis for Commercial Claims aligned to business and portfolio objectives ... Bachelor's degree in mathematics, business, statistics, economics, computer science or equivalent ...

$171K - $210K/yr

Data Engineering, Data Science or Machine Learning * Operations, Security and Data Governance ... Employee Resource Groups EEO/VEVRAA #LI-MH2 #LI-Remote

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Remote Data Science Intern information

What is a Remote Data Science Intern?

A Remote Data Science Intern is a student or recent graduate who works with a company or organization on data science projects while working from a location outside the main office, typically from home. Their tasks often include analyzing large datasets, creating data visualizations, building statistical models, and supporting the team with data-driven insights. Remote internships offer flexibility and allow interns to gain real-world experience in data science while collaborating with teams using digital communication and project management tools. This type of internship helps interns build valuable technical and soft skills that are essential in the evolving data science field.

What types of projects do Remote Data Science Interns typically work on, and how do they collaborate with their teams?

Remote Data Science Interns often work on projects such as data cleaning, exploratory data analysis, building predictive models, or developing data visualizations. Collaboration typically occurs through virtual meetings, shared code repositories, and project management tools, allowing interns to interact regularly with data scientists, engineers, and business analysts. Interns are usually assigned a mentor or supervisor who provides guidance and feedback, helping them align their work with team objectives. This setup not only enhances technical growth but also fosters communication and teamwork skills essential for future roles.

What is the difference between Remote Data Science Intern vs Remote Data Analyst?

AspectRemote Data Science InternRemote Data Analyst
Required CredentialsTypically pursuing or recently completed a degree in Data Science, Computer Science, or related fieldsOften holds a degree in Statistics, Mathematics, or related areas; may have certifications in data analysis tools
Work EnvironmentInternship programs, often part-time or project-based, with mentorshipFull-time or part-time remote roles, focusing on data interpretation and reporting
Employer & Industry UsageUsed by tech companies, startups, and research institutions for entry-level talentCommon across finance, marketing, healthcare, and tech industries for data-driven decision making

The main difference between a Remote Data Science Intern and a Remote Data Analyst lies in experience and scope. Interns are typically students or recent graduates gaining hands-on experience, while Data Analysts are more experienced professionals focused on analyzing and interpreting data to support business decisions. Both roles often work remotely and require familiarity with data tools, but their responsibilities and career stages differ.

What are the key skills and qualifications needed to thrive as a Remote Data Science Intern, and why are they important?

To thrive as a Remote Data Science Intern, you need a solid background in statistics, programming (Python or R), and data analysis, typically supported by coursework in data science or related fields. Familiarity with tools like Jupyter Notebook, SQL databases, and version control systems such as Git is often expected. Strong problem-solving abilities, self-motivation, and clear communication skills help you collaborate effectively and manage tasks independently in a remote setting. These skills ensure you can analyze data accurately, contribute to team projects, and adapt to the demands of remote work environments.
What are the most commonly searched types of Remote Data Science jobs in Alabama? The most popular types of Remote Data Science jobs in Alabama are:
What are popular job titles related to Remote Data Science Intern jobs in Alabama? For Remote Data Science Intern jobs in Alabama, the most frequently searched job titles are:
What cities in Alabama are hiring for Remote Data Science Intern jobs? Cities in Alabama with the most Remote Data Science Intern job openings:
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Huntsville, AL โ€ข Remote

Full-time

Posted 10 days ago


Job description

Overview

FTI Defense is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

FTI Defense delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.

Responsibilities
  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.
Education/Qualifications

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.
  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

ย Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

#LI-KM1

#LI-Remote

Employment Type: FULL_TIME