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Remote Data Science Intern Jobs in Alabama (NOW HIRING)

PingWind

AI Solution Engineer- Ops

Huntsville, AL · On-site +1

Minimum of 4 years of experience in data science, analytics engineering, ML, operations, or AI Hybrid: 3 days of onsite/ 2 days remote Position Description This position supports the Golden Dome ...

PingWind

AI Solution Engineer- Ops

Huntsville, AL · On-site +1

Minimum of 4 years of experience in data science, analytics engineering, ML, operations, or AI Hybrid: 3 days of onsite/ 2 days remote Position Description This position supports the Golden Dome ...

Deckers

United States (Remote) Interested applicants must reside in one of the following approved states ... Bachelor's degree required (Business, Data Science, Analytics, or related field) * Master's degree ...

Pae

Software Engineer

Huntsville, AL · On-site +1

Containerize scientific applications and data processing workflows using Docker and Singularity ... Bachelor's degree with 5+ years' experience (including intern/co-op experience). Master's degree ...

Amentum

Software Engineer

Huntsville, AL · On-site +1

Containerize scientific applications and data processing workflows using Docker and Singularity ... Bachelor's degree with 5+ years' experience (including intern/co-op experience). Master's degree ...

Deckers

United States (Remote) Interested applicants must reside in one of the following approved states ... Bachelor's degree required, preferably in Computer Science, Information Systems, or a related ...

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Remote Data Science Intern information

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 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 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 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 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 job categories do people searching Remote Data Science Intern jobs in Alabama look for? The top searched job categories for Remote Data Science Intern jobs in Alabama 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:
Remote Data Science Intern jobs near you
AI Solution Engineer- Ops

AI Solution Engineer- Ops

PingWind

Huntsville, AL • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 hours ago

Job description

Location: Huntsville, AL or Washington, DC
Required Clearance: TS/SCI Eligible
Required Education: HS/GED
Required Experience: Minimum of 4 years of experience in data science, analytics engineering, ML, operations, or AI

Hybrid: 3 days of onsite/ 2 days remote 

Position Description

This position supports the Golden Dome Supply Chain Enterprise program by executing analytics workflows, data ingestion pipelines, and machine learning model operations within the operations and implementation branch. The engineer works under the technical direction of an Exiger AI Solution Engineer lead, executing ETL processes, analytics production runs, and pipeline maintenance that feed the program's Red Team and Blue Team analytic constructs

Responsibilities

   Execute ETL pipelines for supply chain data ingestion including customer technical data packages, transformation, and loading into the Exiger environment
   Run and monitor ML model inference jobs, flagging anomalies and performance degradation to the lead
   Build and maintain data pipeline automation using Python, SQL, and orchestration frameworks (Airflow, Spark, dbt, or equivalent)
   Produce analytics outputs that feed Red Team vulnerability assessments and Blue Team mitigation planning
   Participate in data quality validation workflows and contribute to confidence scoring documentation
   Support iterative analytics configuration releases based on Government feedback cycles
   Maintain pipeline documentation, run logs, and provenance records per program governance standards


Required Qualifications

    Minimum 4 years of experience in data science, analytics engineering, ML operations, or AI
   Proficiency in Python, SQL, and data pipeline tools (Airflow, Spark, pandas, dbt, or equivalent); working knowledge of relational and cloud data platforms (PostgreSQL, Snowflake, or equivalent)
   Experience with ETL/ELT processes, data transformation, and analytics production workflows across structured and semi-structured data sources
   Familiarity with ML model deployment and monitoring in cloud environments (AWS, Azure, or equivalent)
   Experience working under technical oversight in an integrated government delivery team
   Strong documentation practices and ability to maintain auditable process records

Desired Qualifications

   Experience with ETL/ELT processes, data transformation, and analytics production workflows across structured and semi-structured data sources
   Familiarity with ML model deployment and monitoring in cloud environments (AWS, Azure, or equivalent)
   Experience working under technical oversight in an integrated government delivery team
   Strong documentation practices and ability to maintain auditable process records

Desired Qualifications

   Experience with supply chain data, entity resolution, or risk analytics
   Familiarity with government data handling requirements (CUI, NIST 800-171)
   Experience with containerized deployments (Docker/Kubernetes)
   Experience with PostgreSQL, Snowflake, or similar cloud data warehouse platforms in production analytics environments

About PingWind

PingWind is focused on delivering outstanding services to the federal government. We have extensive experience in the fields of cybersecurity, development, IT infrastructure, supply chain management and other professional services such as system design and continuous improvement. PingWind is an SBA certified Service-Disabled Veteran-Owned Small Business (SDVOSB) with offices in Northern Virginia and Huntsville AL.
www.PingWind.com

Our benefits include:

      Eleven Federal Holidays
      Paid Time Off accrued each pay period
      Parental Leave
      Three medical plan choices with generous employer contribution
      Dental and Vision Insurance
      Company paid Short-Term and Long-Term Disability
      Company paid Life and AD&D Insurance
      401k with competitive matching and vesting schedule 
      Continuing education assistance
      Short Term / Long Term Disability & Life Insurance
      Medical, Dependent Care and Commuter Flexible Spending Accounts
      Employee Assistance Program 
      Wellness benefits include Calm Health app and WellHub gym subsidy (formerly GymPass)
      529 College Savings Plan
      Legal Insurance 
      Pet Insurance

Veterans are encouraged to apply

PingWind, Inc. does not discriminate in employment opportunities, terms, and conditions of employment, or practices on the basis of race, age, gender, religious or political beliefs, national origin or heritage, disability, sexual orientation, or any characteristic protected by law

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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