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Data Science Sustainability Remote information

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$37.5K

$122.7K

$196.5K

How much do data science sustainability remote jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data science sustainability remote in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a Data Science Sustainability Remote job?

A Data Science Sustainability Remote job involves using data analysis and machine learning techniques to address environmental and sustainability challenges while working from a remote location. Professionals in this role analyze large datasets to uncover insights that can improve energy efficiency, reduce waste, and help organizations meet their sustainability goals. They often collaborate with sustainability teams and decision-makers to design data-driven strategies for positive environmental impact. Remote work allows them to perform these tasks from virtually anywhere, providing flexibility and access to a wide range of organizations.

How does a remote Data Science Sustainability role typically contribute to cross-functional teams within an organization?

In a remote Data Science Sustainability role, you'll frequently collaborate with teams such as environmental specialists, product managers, and IT professionals to analyze data and develop models that support the organization's sustainability goals. Effective virtual communication and project management tools are essential, as you may participate in regular video meetings, share progress updates, and co-develop solutions to track and reduce environmental impact. By working closely with diverse departments, you help translate complex data insights into actionable strategies, making your contributions highly visible and impactful across the organization.

What are the key skills and qualifications needed to thrive as a Data Science Sustainability professional working remotely, and why are they important?

To excel as a Data Science Sustainability professional in a remote setting, you need a solid background in data analysis, statistical modeling, and domain knowledge in environmental or sustainability science, typically backed by a relevant degree. Familiarity with programming languages like Python or R, data visualization tools, and experience with sustainability data platforms or certifications such as LEED or GRI is highly valuable. Strong communication, problem-solving abilities, and self-motivation are crucial soft skills for collaborating across virtual teams and translating data insights into actionable strategies. These skills ensure that data-driven decisions effectively support sustainability goals while maintaining productivity and alignment in a remote work environment.

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

AspectData Science Sustainability RemoteData Analyst Sustainability Remote
Required CredentialsBachelor's or higher in Data Science, Statistics, or related fields; certifications like SAS or PythonBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and visualization tools
Work EnvironmentRemote, collaborative teams, often with data engineering and analytics departmentsRemote, focused on data collection, cleaning, and reporting within sustainability projects
Employer & Industry UsageTech companies, environmental agencies, consulting firmsResearch institutions, environmental organizations, corporate sustainability teams

Data Science Sustainability Remote involves advanced analytics, machine learning, and modeling to support sustainability initiatives, requiring technical expertise. Data Analyst Sustainability Remote focuses on analyzing and visualizing sustainability data to inform decisions. Both roles are remote and integral to sustainability efforts but differ in technical complexity and responsibilities.

More about Data Science Sustainability Remote jobs
What cities are hiring for Data Science Sustainability Remote jobs? Cities with the most Data Science Sustainability Remote job openings:
What are the most commonly searched types of Data Science Sustainability jobs? The most popular types of Data Science Sustainability jobs are:
What states have the most Data Science Sustainability Remote jobs? States with the most job openings for Data Science Sustainability Remote jobs include:
What job categories do people searching Data Science Sustainability Remote jobs look for? The top searched job categories for Data Science Sustainability Remote jobs are:
Data Science Sustainability Remote jobs near you
Infographic showing various Data Science Sustainability Remote job openings in the United States as of July 2026, with employment types broken down into 6% Internship, 71% Full Time, 17% Part Time, and 6% Contract. Highlights an 6% In-person, and 94% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Data Science

Data Science

Adidev Technologies Inc

San Francisco, CA • Remote

Full-time

Re-posted 24 days 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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