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Remote Conservation Data Science Jobs in Philadelphia, PA

Soni Resources

Data Scientist

Conshohocken, PA · On-site +1

$175K/yr

... Data Science + Data Engineering) Location: Remote (Preference for Northeast/Mid-Atlantic; monthly travel to Plymouth Meeting, PA as needed) Our client is building a data-driven culture where ...

Eastern University

Adjunct Faculty- Data Science

PA · On-site +1

Remote Optional Job Number: 515 Department: Data Science - (College of Health and Sciences) Opening Date: 01/25/2024 Join our vibrant community of dedicated faculty and staff who work to create a ...

Bread Financial

Lead Data Scientist

Chadds Ford, PA · On-site +1

$144K - $250K/yr

Bachelor's Degree in Statistics, Mathematics, Engineering, Data Science, Computer Science, or ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

QVC

Data Engineer

West Chester, PA · Remote

$108K - $130K/yr

Where You'll Work This role is remote; job seekers must reside in one of the following states to be ... Create data products for analytics and data science teams to improve their productivity and ...

Lancesoft INC

Senior Data Scientist

Titusville, NJ · Remote

$65 - $68/hr

Role can be HYBRID or REMOTE, but must be in EST time zone, prefers the candidate lives in NJ or PA ... This candidate will provide technical support to the MSAT Material Science team on a variety of ...

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All JobsConservation Data Science JobsRemote Conservation Data Science JobsRemote Conservation Data Science Jobs in Philadelphia, PA

Remote Conservation Data Science information

See Philadelphia, PA salary details

$37.8K

$123.9K

$198.3K

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

As of Aug 6, 2026, the average yearly pay for remote conservation data science in Philadelphia, PA is $123,854.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,400.00 and $137,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a remote conservation data scientist?

To thrive as a Remote Conservation Data Scientist, you need expertise in data analysis, ecological modeling, and a strong background in environmental science or a related field, often supported by an advanced degree. Proficiency with programming languages like Python or R, GIS tools (such as ArcGIS or QGIS), and relevant data management systems is essential. Excellent problem-solving, communication, and collaboration skills are crucial for translating data insights into actionable conservation strategies with remote teams. These abilities enable effective data-driven decision-making and foster impactful conservation outcomes across diverse and distributed environments.

How does a remote conservation data scientist typically collaborate with field teams and stakeholders?

Remote conservation data scientists often rely on digital communication tools—such as video calls, shared databases, and project management platforms—to work closely with field researchers, conservation managers, and external partners. While they may not be physically present at field sites, they regularly interpret, analyze, and visualize data collected on the ground, providing actionable insights for ongoing projects. Regular virtual meetings are common for aligning on project goals, discussing data quality, and adapting analytical approaches based on field realities. This collaborative structure ensures that data-driven recommendations are both relevant and grounded in real-world conservation challenges.

What is a remote conservation data scientist?

A Remote Conservation Data Scientist is a professional who analyzes environmental data to support conservation efforts, often working from a location outside of a traditional office or onsite fieldwork setting. They use data science techniques such as statistical analysis, machine learning, and geographic information systems (GIS) to interpret data related to biodiversity, ecosystems, wildlife populations, and climate change. Their work helps inform conservation policies, resource management, and strategies to protect natural habitats. Remote work in this field relies heavily on digital collaboration tools and access to large datasets. These scientists often partner with non-profits, government agencies, or research organizations to tackle global conservation challenges.
What are the most commonly searched types of Conservation Data Science jobs in Philadelphia, PA? The most popular types of Conservation Data Science jobs in Philadelphia, PA are:
What job categories do people searching Remote Conservation Data Science jobs in Philadelphia, PA look for? The top searched job categories for Remote Conservation Data Science jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Remote Conservation Data Science jobs? Cities near Philadelphia, PA with the most Remote Conservation Data Science job openings:
Remote Conservation Data Science jobs near you
Infographic showing various Remote Conservation Data Science job openings in Philadelphia, PA as of August 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% Remote job distribution, with an average salary of $123,854 per year, or $59.5 per hour.

Senior Director of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Re-posted 19 hours ago

Job description

At Forbes Advisor, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance so they can make informed decisions they feel confident in and get back to doing the things they care about most.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Forbes Advisor boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Forbes Advisor's global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
Our Data & Analytics organisation builds the products, platforms and intelligence that power every marketing, product and commercial decision across the business. We're looking for a Data Science leader who believes machine learning only creates value when it changes business decisions.
This is an opportunity to build and lead a commercially driven Data Science function that delivers measurable improvements in customer acquisition, marketing performance and long-term business growth.
You'll lead a growing team of Data Scientists while partnering closely with Engineering, Analytics, Product and Commercial teams to ensure predictive models become trusted, production-ready products that drive measurable commercial outcomes. As we continue investing in first-party data, AI, machine learning and advanced marketing measurement, we're looking for an experienced Data Science leader to help shape the next phase of our commercial Data Science capability.
Responsibilties:
  • Commercial Data Science: Lead the strategy and delivery of predictive models that improve customer acquisition, marketing performance and long-term commercial value. You'll shape capabilities including lifetime value modelling, propensity modelling, customer segmentation, forecasting and value-based bidding, ensuring every model is linked to measurable business outcomes.
  • Marketing Science & Decision Science: Partner with Marketing, Product and Commercial teams to apply Data Science to real business problems. You'll help define how predictive analytics, experimentation and AI improve campaign performance, customer understanding and strategic decision making across platforms including Google and Meta.
  • Production Data Science: Work closely with Engineering and ML Ops to ensure models become reliable, production-ready products rather than one-off analyses. You'll champion reproducible experimentation, scalable deployment, model monitoring, retraining strategies and continuous improvement throughout the model lifecycle.
  • Leadership & Stakeholder Management: Lead and develop a growing team of Data Scientists while building trusted relationships across the business. You'll translate complex modelling into clear commercial recommendations, influence senior stakeholders through evidence, and help establish Data Science as a trusted driver of business strategy and commercial growth.
  • Innovation & Industry Leadership: Represent Forbes in strategic conversations with technology partners including Google and Meta while staying connected to advances in AI, machine learning and marketing science. You'll evaluate emerging technologies, bring new ideas into the organisation and help ensure our Data Science capability remains commercially relevant and technically leading.

Qualifications:
  • Experience leading commercial Data Science, Marketing Science or Decision Science teams.
  • Strong expertise in predictive analytics, customer analytics, machine learning and statistical modelling.
  • Experience applying Data Science to marketing performance, customer acquisition, lifetime value or value-based bidding.
  • Experience productionising machine learning solutions within modern cloud environments and working closely with Engineering and ML Ops teams.
  • Strong understanding of SQL, Python and modern machine learning frameworks.
  • Experience working with Google Ads, Meta or other major advertising platforms.
  • Excellent stakeholder management and communication skills, with the ability to influence both technical and commercial audiences.
  • Experience building and developing high-performing Data Science teams.
  • Strong commercial judgement, balancing technical excellence with measurable business impact.
  • A pragmatic approach to AI, applying emerging technologies where they create genuine commercial value.

Nice to Have
  • Experience within affiliate marketing, digital publishing or lead-generation businesses.
  • Experience working in financial services, insurance or regulated industries.
  • Experience working directly with Google or Meta Data Science teams.
  • Experience with attribution modelling and marketing measurement.
  • Experience building optimisation algorithms for DSPs or advertising platforms.
  • Experience with causal inference, experimentation frameworks or incrementality testing.
  • Experience forecasting marketing or commercial performance.
  • Experience with Vertex AI or equivalent cloud-based machine learning platforms.

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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