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Environmental Data Science Jobs in Delaware (NOW HIRING)

Sallie Mae

Senior Manager, Statistical Modeling

Newark, DE · On-site

$85K - $104K/yr

... Data Science, Machine Learning, or a related field. * 5+ years of experience in statistical modeling, including hands-on experience developing and deploying models in production environments.

Aumni

Applied AI/ML - Vice President

Wilmington, DE · On-site

$120 - $160/hr

This is a unique opportunity to apply your skills and leadership in a dynamic environment, directly ... Work with product managers, data scientists, ML engineers, and other stakeholders to understand ...

Bancorp Bank

$150 - $200/hr

... Data Science, Operations, Risk, Compliance, Legal, Information Security, Financial Crimes, and business leaders to operationalize AI solutions in production environments. * Establishes enterprise ...

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All JobsEnvironmental Data Science JobsEnvironmental Data Science Jobs in Delaware

Environmental Data Science information

See Delaware salary details

$37.5K

$122.8K

$196.7K

How much do environmental data science jobs pay per year?

As of Aug 12, 2026, the average yearly pay for environmental data science in Delaware is $122,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,600.00 and $136,100.00 per year, depending on experience, location, and employer.

Is environmental data science a good major?

Environmental data science is a strong major for those interested in analyzing environmental data, using tools like GIS and statistical software. It prepares students for roles in environmental monitoring, research, and policy, often requiring skills in programming, data analysis, and environmental science. Job prospects are growing as organizations seek data-driven solutions to environmental challenges.

What does an environmental data scientist do?

An environmental data scientist analyzes environmental data to identify patterns, assess environmental risks, and support decision-making. They use statistical tools, programming languages like Python or R, and GIS software to interpret data related to climate, pollution, and natural resources, often working with large datasets and models to inform environmental policies and practices.

What is environmental data science?

Environmental Data Science is an interdisciplinary field that uses statistical, computational, and analytical techniques to collect, analyze, and interpret large sets of data related to the environment. Professionals in this field work on issues like climate change, pollution, biodiversity, and natural resource management by extracting meaningful insights from complex environmental datasets. Their work supports decision-making for policy, conservation, and sustainability initiatives. Environmental data scientists often collaborate with ecologists, geographers, and policymakers to address environmental challenges using data-driven approaches.

What are some common challenges faced by environmental data scientists when working with real-world datasets?

Environmental data scientists often encounter challenges such as incomplete or inconsistent data, varying data formats, and the need to integrate information from multiple sources like sensors, satellites, and field observations. Addressing missing values, data quality issues, and ensuring proper geospatial alignment can be time-consuming but is essential for producing reliable analyses. Collaboration with domain experts and stakeholders is frequently required to interpret findings and ensure that the results are actionable for environmental policy or management decisions.

What is the difference between Environmental Data Science vs Environmental Data Analyst?

AspectEnvironmental Data ScienceEnvironmental Data Analyst
Required CredentialsTypically requires a degree in data science, environmental science, or related fields; often includes programming and statistical certificationsUsually requires a degree in environmental science, geography, or related fields; may include basic data analysis certifications
Work EnvironmentResearch labs, data centers, environmental agencies, or consulting firmsEnvironmental agencies, research organizations, or consulting firms
Employer & Industry UsageUsed in environmental research, climate modeling, and policy analysisUsed in environmental monitoring, reporting, and data interpretation

Environmental Data Science focuses on developing models and algorithms to analyze complex environmental data, often requiring advanced programming skills. In contrast, Environmental Data Analysts primarily interpret and visualize environmental data to support decision-making. Both roles are vital but differ in technical depth and scope.

What are the key skills and qualifications needed to thrive as an environmental data scientist, and why are they important?

To thrive as an Environmental Data Scientist, you need strong quantitative skills, expertise in environmental science, and a relevant degree in data science, statistics, or a related field. Familiarity with data analysis tools such as Python, R, GIS software, and experience with large datasets or machine learning techniques is typical. Exceptional problem-solving abilities, communication skills, and attention to detail set top performers apart in this field. These competencies are crucial for effectively interpreting complex environmental data, informing policy, and driving impactful sustainability initiatives.
What are the most commonly searched types of Environmental Data Science jobs in Delaware? The most popular types of Environmental Data Science jobs in Delaware are:
What are popular job titles related to Environmental Data Science jobs in Delaware? For Environmental Data Science jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Environmental Data Science jobs in Delaware look for? The top searched job categories for Environmental Data Science jobs in Delaware are:
Environmental Data Science jobs near you
Infographic showing various Environmental Data Science job openings in Delaware as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $122,844 per year, or $59.1 per hour.

Senior Manager, Statistical Modeling

Sallie Mae Bank

Newark, DE • On-site

$85K - $105K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 hours ago

Job description

When you join Sallie Mae, you become a champion for all students.
We're on a mission to power confidence as students begin their unique journey. To help them plan their higher education, successfully finish, and prepare for life after school. To help them Start smart. Learn big.
Students need guidance navigating this important time in their life. They need someone who acknowledges that their education path is unique. They need a partner willing to evolve and not only meet but surpass their expectations. We're changing. Because students need a better way.
We're looking for people who are excited to drive this transformation. To break barriers and think of new ways to adapt, help, and create better experiences for students-and for each other.
This is where diverse backgrounds, beliefs, and perspectives matter. It's where you're empowered to bring your authentic self to work.
Feeling your best allows you to do your best. Our benefits take care of the whole you-from physical and mental to financial and professional. You'll get opportunities to further your education and career, support for you and your family (including your pets!), paid time off to volunteer for the things that matter to you, and more.
We're obsessed with impact and making a real difference. For us, that means putting relationships first, asking "why not?" when tackling challenges, and continuously learning new skills.
Come do more than join something, change something. For students, for future generations, for the future of education.
What You'll Contribute
The Senior Manager, Statistical Modeling will be responsible for developing and implementing advanced statistical models and methodologies to analyze complex data sets, extract insights, and provide actionable recommendations.
What You'll Do
  • Design, develop and implement statistical and machine learning models and algorithms, aligning with organizational goals and digital transformation initiatives.
  • Foster a collaborative and innovative work environment that encourages knowledge sharing, professional growth, and continuous improvement.
  • Oversee the full model development and machine learning lifecycle: data collection, preprocessing, feature engineering, model development, deployment, and monitoring.
  • Collaborate with cross-functional teams to translate business needs into effective modeling solutions.
  • Ensure models are robust, reliable, and compliant with security, privacy, and governance standards.
  • Develop and implement evaluation and validation procedures to ensure the accuracy, reliability, and scalability of statistical models.
  • Generate regular reports and presentations to communicate results, insights, and recommendations to senior leadership and relevant stakeholders.
  • Communicate results, insights, and recommendations to stakeholders through reports and presentations.
  • Stay current with advancements in machine learning and data science, and evaluate new tools and technologies for adoption.

The above information is intended to describe the general nature and level of work performed by employees assigned to this job; it is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees in this role.
What you have
Minimum: Indicate minimum education, skills and experience required.
  • Master's degree in Statistics, Mathematics, Data Science, Computer Science, Data Science, Machine Learning, or a related field.
  • 5+ years of experience in statistical modeling, including hands-on experience developing and deploying models in production environments.
  • Proficiency in statistical programming languages such as Python, R, or SAS, and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Strong understanding of statistical modeling techniques, such as regression analysis, time series analysis, predictive modeling, and machine learning algorithms(supervised, unsupervised, deep learning, reinforcement learning).
  • Experience with cloud-based platforms (e.g., AWS, Azure, Google Cloud).
  • Familiarity with data engineering, data visualization, and model evaluation techniques.
  • Excellent analytical and problem-solving abilities, with keen attention to detail.
  • Effective communication and interpersonal skills, with the ability to present technical concepts to non-technical audiences.

Preferred: Indicate "nice to haves" regarding education, skills, and experience.
  • Doctorate's degree in Statistics, Mathematics, Data Science, Computer Science, Machine Learning, or a related field.
  • 8+ years of experience in statistical modeling, machine learning, or data science, including managing large-scale ML projects.
  • Experience with MLOps, containerization (Docker, Kubernetes), and deploying models in enterprise environments.
  • Experience with data governance, security, and compliance in ML projects.

The Americans with Disabilities Act
The Americans with Disabilities Act of 1990 (ADA) prohibits discrimination by employers, in compensation and employment opportunities, against qualified individuals with disabilities who, with or without reasonable accommodation, can perform the "essential functions" of a job. A function may be essential for any of several reasons, including: the job exists to perform that function, the employee holding the job was hired for his/her expertise in performing the function, or only a limited number of employees are available to perform that function.
Feeling your best helps you do your best:
Our benefits take care of the whole you-so you can build your work around your life (not the other way around!).
  • Competitive base salaries
  • Bonus incentives
  • Generous PTO, Floating Holidays and 12 Federal Holidays observed
  • Support for financial-well-being and retirement 401k with employer match
  • Comprehensive medical, dental, vision, hospital indemnity, critical illness, pet insurance and more
  • Employer paid short-term/long-term disability and basic life insurance
  • Flexible hybrid working arrangements.
  • Paid parental leave and adoption reimbursement programs
  • Free access to on-site staffed fitness centers (in Delaware) and gym subsidy (for locations outside Delaware)
  • Confidential counseling support (EAP), Health Advocacy services and Wellness program with financial incentives
  • Tuition Reimbursement and Family Scholarship Programs
  • Career development and training opportunities

Not the right fit? Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!
Sallie Mae is proud to be an equal opportunity (EEO) employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, sexual orientation, national origin, age, genetic information, gender identity, disability, Veteran status or any other characteristic protected by federal, state or local law. Click here to view the U.S. Pay Transparency Policy, here for federal job applicant notices, and here to view the California Employee Privacy Notice.
Reasonable accommodations are available for applicants with disabilities in all phases of the application and employment process. To request an accommodation please call and choose option 9. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

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