Remote Staff Scientist Jobs
Remote staff scientist jobs are in active demand across the U.S., with remote-first firms and distributed research teams hiring across biotech, pharmaceutical, and tech sectors. Employers hiring remotely right now include General Motors (GM), The Predictive Index, and Root Insurance Company. See the openings below and apply to the ones that match your experience.
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Showing 5 of 30+ Remote Staff Scientist jobs
Earnest empowers ambitious professionals to make confident financial decisions and build the life they envision.
Earnies are committed to helping borrowers move forward with confidence by offering smarter borrowing options with a clearer path to taking control of their debt. If you're as passionate as we are about our mission, read more below, and let's build something great together.
The Staff Data Scientist will report to Sr. Manager, Data Science + Pricing.
You will be the primary owner of risk data science at Earnest, driving the development of sophisticated credit risk, underwriting, fraud detection, collections, and loss forecasting frameworks that directly shape portfolio health and the unit economics of our lending products. You will lead high-impact modeling initiatives, mentor junior team members, and serve as a key cross-functional partner to senior stakeholders across Risk, Product, Capital Markets, Engineering, and Finance.
As the Staff Data Scientist, you will:
- Own the end-to-end development and delivery of Risk Science systems — including credit risk scoring, default prediction (PD/LGD), fraud detection, and collection scores — that balance loan volume growth with risk-adjusted profitability.
- Lead the design, backtesting, and validation of credit risk models and loss forecasting frameworks, applying advanced statistical techniques and machine learning to evaluate portfolio performance.
- Serve as the internal subject matter expert on credit risk modeling, loss dynamics, and risk-based decisioning engines, shaping how the organization approaches credit policy and risk management.
- Independently lead high-visibility, cross-functional risk modeling projects from conception through production deployment, proactively managing timelines and stakeholder expectations.
- Translate complex risk models, loss projections, and analytical findings into clear, compelling narratives for senior leadership, the Risk Committee, and non-technical stakeholders.
- Mentor and provide technical guidance to junior and senior data scientists, helping establish modeling standards, robust governance, and a culture of analytical rigor.
- Partner closely with Risk, Pricing, Product, Capital Markets, Engineering, and Compliance leadership to align risk strategies with company-wide growth, funding requirements, and regulatory obligations.
- Oversee the deployment of scalable, production-grade risk and fraud pipelines in collaboration with data and ML engineering teams, including automated monitoring, stress testing, and alerting.
- Partner closely with the MRM team for best practices in model validation, fair lending analysis, model governance, and comprehensive technical documentation across the data science team.
About You:
- 8+ years of experience in Python/R and SQL.
- 7+ years of professional experience in quantitative risk modeling, credit risk analytics, fraud analytics, or applied data science
- Master's/PhD in Economics, Statistics, Computer Science, Operations Research, or a related quantitative field
- Prior experience in consumer lending, fintech, or financial services with direct technical ownership of credit underwriting or fraud models.
- Strong expertise in credit risk modeling, default prediction (PD, LGD, EAD), survival analysis, machine learning algorithms (e.g., Gradient Boosted Trees, Logistic Regression), and risk-adjusted return frameworks.
- Deep proficiency in model lifecycle management, model validation, backtesting, and monitoring applied to credit or fraud risk environments.
- Proven track record of independently owning and delivering complex, cross-functional modeling initiatives end-to-end.
- Experience mentoring/managing junior data scientists and contributing to team-wide technical and governance standards.
- Strong communication skills with the ability to influence stakeholders and present technical concepts clearly to senior audiences.
Even Better:
- Solid understanding of financial metrics, consumer credit regulations (e.g., FCRA, ECOA/Fair Lending).
- Experience with cloud production platforms such as AWS, GCP, or Azure.
- Proficiency with modern data engineering and analytics tooling such as Looker, Airflow, and dbt.
- Experience leveraging non-traditional data sources or LLM/NLP tools applied to underwriting, fraud detection, or document processing.
Where:
- This role will be based in the US.
Compensation:
A little about our pay philosophy: We take pride in compensating our employees fairly and equitably. We are showcasing a range of your potential base salary based on the roles location. The successful candidate's starting pay will also be determined based on job-related qualifications, internal compensation, candidate location and budget. This range may be modified in the future.
Salary Range: $216k - $262k USD. Employees are also eligible for an annual performance-based bonus and equity.
#LI- SM
Earnest believes in enabling our employees to live their best lives. We offer a variety of perks and competitive benefits, including:
- Health, Dental, & Vision benefits plus savings plans
- Mac computers + work-from-home stipend to set up your home office
- Monthly internet and phone reimbursement
- Employee Stock Purchase Plan
- Restricted Stock Units (RSUs)
- 401(k) plan to help you save for retirement plus a company match
- Robust tuition reimbursement program
- $1,000 travel perk on each Earnie-versary to anywhere in the world
- Competitive days of annual PTO
- Competitive parental leave
What Makes an Earnie:
At Earnest, our people bring our cultural principles to life. These principles define how we work, how we win, and what we expect of ourselves and each other:
- Every Second Counts: Speed is our competitive advantage. Our customers need better solutions, and the faster we execute, the greater our chance of success.
- Choose To Do Hard Things: We win by tackling the hard things that others avoid, fueled by grit and resilience.
- Pursue Excellence: Great companies, teams, and individuals never settle and are proud of the work that they do. What's good enough today won't be good enough tomorrow. Excellence isn't a destination; it's a mindset of continuous improvement.
- Lead Together: Our success comes from how we work together. Leadership is not about titles—it is about action. We take ownership, drive results, and move forward as a team.
- Don't Take Yourself Too Seriously: We take our work seriously, not ourselves. The stakes are high, but a sense of humor keeps us grounded, creative, and resilient.
At Earnest, we are committed to building an environment where our employees feel included, valued, and heard. Our belief is that a strong commitment to diversity, inclusion, equity, and belonging enables us to move forward with our mission. We are dedicated to adding new perspectives to the team and encourage anyone to apply if your experience is close to what we are looking for.
Earnest provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, veteran status, disability or genetics. Qualified applicants with criminal histories will be considered for the position in a manner consistent with the Fair Chance Ordinance.
Earnest empowers ambitious professionals to make confident financial decisions and build the life they envision.
Earnies are committed to helping borrowers move forward with confidence by offering smarter borrowing options with a clearer path to taking control of their debt. If you're as passionate as we are about our mission, read more below, and let's build something great together.
The Staff Data Scientist will report to Sr. Manager, Data Science + Pricing.
You will be the primary owner of risk data science at Earnest, driving the development of sophisticated credit risk, underwriting, fraud detection, collections, and loss forecasting frameworks that directly shape portfolio health and the unit economics of our lending products. You will lead high-impact modeling initiatives, mentor junior team members, and serve as a key cross-functional partner to senior stakeholders across Risk, Product, Capital Markets, Engineering, and Finance.
As the Staff Data Scientist, you will:
- Own the end-to-end development and delivery of Risk Science systems — including credit risk scoring, default prediction (PD/LGD), fraud detection, and collection scores — that balance loan volume growth with risk-adjusted profitability.
- Lead the design, backtesting, and validation of credit risk models and loss forecasting frameworks, applying advanced statistical techniques and machine learning to evaluate portfolio performance.
- Serve as the internal subject matter expert on credit risk modeling, loss dynamics, and risk-based decisioning engines, shaping how the organization approaches credit policy and risk management.
- Independently lead high-visibility, cross-functional risk modeling projects from conception through production deployment, proactively managing timelines and stakeholder expectations.
- Translate complex risk models, loss projections, and analytical findings into clear, compelling narratives for senior leadership, the Risk Committee, and non-technical stakeholders.
- Mentor and provide technical guidance to junior and senior data scientists, helping establish modeling standards, robust governance, and a culture of analytical rigor.
- Partner closely with Risk, Pricing, Product, Capital Markets, Engineering, and Compliance leadership to align risk strategies with company-wide growth, funding requirements, and regulatory obligations.
- Oversee the deployment of scalable, production-grade risk and fraud pipelines in collaboration with data and ML engineering teams, including automated monitoring, stress testing, and alerting.
- Partner closely with the MRM team for best practices in model validation, fair lending analysis, model governance, and comprehensive technical documentation across the data science team.
About You:
- 8+ years of experience in Python/R and SQL.
- 7+ years of professional experience in quantitative risk modeling, credit risk analytics, fraud analytics, or applied data science
- Master's/PhD in Economics, Statistics, Computer Science, Operations Research, or a related quantitative field
- Prior experience in consumer lending, fintech, or financial services with direct technical ownership of credit underwriting or fraud models.
- Strong expertise in credit risk modeling, default prediction (PD, LGD, EAD), survival analysis, machine learning algorithms (e.g., Gradient Boosted Trees, Logistic Regression), and risk-adjusted return frameworks.
- Deep proficiency in model lifecycle management, model validation, backtesting, and monitoring applied to credit or fraud risk environments.
- Proven track record of independently owning and delivering complex, cross-functional modeling initiatives end-to-end.
- Experience mentoring/managing junior data scientists and contributing to team-wide technical and governance standards.
- Strong communication skills with the ability to influence stakeholders and present technical concepts clearly to senior audiences.
Even Better:
- Solid understanding of financial metrics, consumer credit regulations (e.g., FCRA, ECOA/Fair Lending).
- Experience with cloud production platforms such as AWS, GCP, or Azure.
- Proficiency with modern data engineering and analytics tooling such as Looker, Airflow, and dbt.
- Experience leveraging non-traditional data sources or LLM/NLP tools applied to underwriting, fraud detection, or document processing.
Where:
- This role will be based in the US.
Compensation:
A little about our pay philosophy: We take pride in compensating our employees fairly and equitably. We are showcasing a range of your potential base salary based on the roles location. The successful candidate's starting pay will also be determined based on job-related qualifications, internal compensation, candidate location and budget. This range may be modified in the future.
Salary Range: $216k - $262k USD. Employees are also eligible for an annual performance-based bonus and equity.
#LI- SM
Earnest believes in enabling our employees to live their best lives. We offer a variety of perks and competitive benefits, including:
- Health, Dental, & Vision benefits plus savings plans
- Mac computers + work-from-home stipend to set up your home office
- Monthly internet and phone reimbursement
- Employee Stock Purchase Plan
- Restricted Stock Units (RSUs)
- 401(k) plan to help you save for retirement plus a company match
- Robust tuition reimbursement program
- $1,000 travel perk on each Earnie-versary to anywhere in the world
- Competitive days of annual PTO
- Competitive parental leave
What Makes an Earnie:
At Earnest, our people bring our cultural principles to life. These principles define how we work, how we win, and what we expect of ourselves and each other:
- Every Second Counts: Speed is our competitive advantage. Our customers need better solutions, and the faster we execute, the greater our chance of success.
- Choose To Do Hard Things: We win by tackling the hard things that others avoid, fueled by grit and resilience.
- Pursue Excellence: Great companies, teams, and individuals never settle and are proud of the work that they do. What's good enough today won't be good enough tomorrow. Excellence isn't a destination; it's a mindset of continuous improvement.
- Lead Together: Our success comes from how we work together. Leadership is not about titles—it is about action. We take ownership, drive results, and move forward as a team.
- Don't Take Yourself Too Seriously: We take our work seriously, not ourselves. The stakes are high, but a sense of humor keeps us grounded, creative, and resilient.
At Earnest, we are committed to building an environment where our employees feel included, valued, and heard. Our belief is that a strong commitment to diversity, inclusion, equity, and belonging enables us to move forward with our mission. We are dedicated to adding new perspectives to the team and encourage anyone to apply if your experience is close to what we are looking for.
Earnest provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, veteran status, disability or genetics. Qualified applicants with criminal histories will be considered for the position in a manner consistent with the Fair Chance Ordinance.
See All 30 Remote Staff Scientist Jobs
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Find Remote Staff Scientist JobsRemote Staff Scientist Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Science & Research
- Hospitality & Tourism
- Artificial Intelligence
What Employers Look For
The qualifications that appear most often in remote staff scientist jobs.
- PhD in a life science, chemical science, or related field
- Proficiency with one or more specialized laboratory platforms or analytical instruments
- Experience independently designing and executing experimental protocols
- Demonstrated record of peer-reviewed publications or technical reports
- Ability to mentor junior researchers, technicians, or graduate students
- Familiarity with data analysis tools such as Python, R, GraphPad Prism, or FlowJo
Tips for Your Remote Staff Scientist Job Search
Apply early to remote roles that fit
Migrate Mate lists remote staff scientist openings from across the U.S. in one place, so you can find roles that match your research background and apply directly without sorting through unrelated postings.
Demonstrate async communication in your application
Remote research teams run on written updates, documented decisions, and self-managed timelines. Use your cover letter and any writing samples to show you communicate complex scientific findings clearly without real-time back-and-forth.
Highlight independent project ownership on your resume
Remote staff scientist hiring managers look for candidates who have driven projects from hypothesis to deliverable without close supervision. Name the specific research questions you owned, the methods you chose, and the outcomes you produced.
Prepare for asynchronous technical screens
Many remote-first employers send take-home data analysis tasks or written case studies instead of live coding interviews. Practice explaining your reasoning in written form and presenting results clearly in a document or slide deck, not just verbally.
Remote Staff Scientist Jobs: Frequently Asked Questions
How do I get a remote staff scientist job?
Target companies with established remote research teams, particularly remote-first biotech firms, contract research organizations, and tech companies with distributed science functions. Remote employers screen hard for self-direction, clear async written communication, and the ability to collaborate across time zones without in-person oversight. A strong publication record, documented independent project ownership, and comfort with tools like electronic lab notebooks and collaborative data platforms give candidates a clear edge.
Which companies hire remote staff scientists?
Employers currently hiring remote staff scientists include General Motors (GM), The Predictive Index, and Root Insurance Company, per current remote listings on Migrate Mate as of November 2026. The roles tend to cluster at remote-first biotech and pharmaceutical companies, distributed contract research organizations, and technology firms running computational or data science research functions.
Can you get a remote staff scientist job with no experience?
Yes, but remote entry-level staff scientist roles are harder to land because employers expect you to work independently from day one with minimal in-person mentorship. Your strongest path is through companies with structured remote onboarding in computational biology, bioinformatics, or data-heavy research. Demonstrating independent projects, open-source contributions, or graduate research with clear solo deliverables can substitute meaningfully for formal job experience.
Do you need a degree for remote staff scientist jobs?
Usually, but the weight placed on the degree depends on the specialization. Most remote staff scientist roles expect at least a master's degree, and many prefer a PhD for independent research functions. Remote employers do weigh demonstrated skills alongside credentials, and candidates with strong portfolios of published work, computational research, or documented project outcomes can offset a less traditional academic background.
Which industries hire the most remote staff scientists?
Most remote staff scientist openings sit in Technology & Software, Science & Research, and Hospitality & Tourism, per current remote listings on Migrate Mate as of November 2026. Those sectors hire remotely because their research workflows, data analysis pipelines, and cross-functional collaboration adapt well to distributed team structures.
See All 30 Remote Staff Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Staff Scientist Jobs