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What is a Data Science Remote Volunteer job?

A Data Science Remote Volunteer job involves assisting organizations with data-related tasks such as data cleaning, analysis, and machine learning model development, all while working remotely. Volunteers typically help nonprofits, research institutions, or startups by leveraging data to drive insights and decision-making. This role allows individuals to gain practical experience, contribute to meaningful projects, and improve their data science skills without being in a paid position.

What are the key skills and qualifications needed to thrive in the Data Science Remote Volunteer position, and why are they important?

To thrive as a Data Science Remote Volunteer, you need a solid understanding of statistical analysis, data cleaning, and programming—typically with experience in Python or R and familiarity with machine learning concepts. Proficiency with data visualization tools like Tableau or Power BI, and knowledge of database systems such as SQL, is highly valuable; certifications like Google Data Analytics or DataCamp can further strengthen your candidacy. Strong communication skills, self-motivation, and the ability to collaborate virtually with diverse teams are essential soft skills. These abilities are crucial for delivering impactful insights, contributing effectively in remote settings, and supporting organizational goals even outside a traditional paid environment.

What does a typical project or task involve for a Data Science Remote Volunteer?

As a Data Science Remote Volunteer, your typical tasks may include cleaning and organizing datasets, developing predictive models, visualizing data findings, and preparing reports for stakeholders. You might collaborate with other volunteers or staff members using collaborative tools like Slack, Zoom, or GitHub to work on projects ranging from social impact data analysis to supporting nonprofit decision-making. Projects often involve both individual research and team-based problem solving, giving you experience in each stage of the data science workflow. This volunteer opportunity is a great way to gain real-world experience, expand your professional network, and make a tangible difference through data-driven insights.

More about Data Science Remote Volunteer jobs
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What job categories do people searching Data Science Remote Volunteer jobs look for? The top searched job categories for Data Science Remote Volunteer jobs are:
Data Science Remote Volunteer jobs near you
Infographic showing various Data Science Remote Volunteer job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 84% Full Time, 9% Part Time, 4% Contract, and 1% Nights. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.
Data Science

Data Science

Adidev Technologies Inc

San Francisco, CA • Remote

Full-time

Posted 2 hours ago

Job description

Adidev Technologies Inc 

www.adidevtechnologies.com

URGENT HIRE - HIRING PROCESS - 24-48 HOURS!

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.

If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.

Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly

 

Job Description

  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline


Must  have 

  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS

  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred

  • At least 2 yrs of relevant experience in Data Science


SKILLS

  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits

  • Competitive Salary

  • Paid Relocation

  • Remote Support

  • Guaranteed Regular Salary Reviews

  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

Employment Type: FULL_TIME

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