Remote Senior Staff Data Scientist Jobs
Remote senior staff data scientist jobs are in active demand across the U.S., with remote-first firms and distributed data teams hiring at the senior and staff levels in technology, finance, healthcare, and retail analytics. Employers posting remote roles right now include Machinify, Root Insurance Company, and Block. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 23+ Remote Senior Staff Data 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 23 Remote Senior Staff Data Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsRemote Senior Staff Data Scientist Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Artificial Intelligence
- Hospitality & Tourism
What Employers Look For
The qualifications that appear most often in remote senior staff data scientist jobs.
- PhD or MS in statistics, computer science, or a related quantitative field with 8 or more years of industry experience
- Deep proficiency in Python and SQL with production-level experience in machine learning frameworks such as PyTorch or TensorFlow
- Experience designing and analyzing large-scale A/B tests and causal inference studies in high-traffic environments
- Demonstrated ability to lead technical strategy and mentor senior data scientists across multiple project teams
- Hands-on experience with distributed computing platforms such as Spark, Databricks, or equivalent cloud-native ML infrastructure
- Strong communication skills with a history of presenting modeling recommendations to executive or cross-functional stakeholders
Tips for Your Remote Senior Staff Data Scientist Job Search
Apply early to remote roles that fit
Migrate Mate lists remote senior staff data scientist openings from across the U.S. in one place. Check it regularly and apply directly to roles that match your stack and scope, since remote positions at this level fill quickly when a strong candidate pool is available.
Build a portfolio that shows async leadership
Remote employers at the senior staff level want evidence you can lead data initiatives without daily oversight. Document a project end-to-end, including your decision-making process, tradeoffs, and results, in a format a hiring manager can read without a walkthrough from you.
Sharpen your written technical communication
Remote senior staff data scientists run alignment across engineering, product, and leadership through writing. Practice writing crisp design documents, model cards, and experiment summaries that a non-technical stakeholder can act on without a follow-up meeting.
Target companies with distributed data teams
Remote-first technology companies, fintech platforms, and healthcare analytics organizations hire senior staff data scientists with established remote infrastructure. Prioritize employers whose job postings reference async standups, distributed team structures, or documentation-first cultures, since those signal genuine remote readiness.
Remote Senior Staff Data Scientist Jobs: Frequently Asked Questions
How do I get a remote senior staff data scientist job?
Target remote-first companies and distributed teams in sectors like technology, fintech, and healthcare that regularly hire senior staff data scientists without location requirements. Remote employers screen hard for self-direction, strong async written communication, and the ability to lead cross-functional data initiatives without in-person oversight. Concrete experience with distributed workflows, clear documentation habits, and a portfolio of end-to-end ML or analytics projects gives your application a real edge.
Which companies hire remote senior staff data scientists?
Remote senior staff data scientist roles are posted by Machinify, Root Insurance Company, and Block and others right now, based on current remote listings on Migrate Mate as of November 2026. Remote-first technology companies, distributed fintech platforms, and large healthcare and insurance organizations account for the bulk of these openings.
Can you get a remote senior staff data scientist job with no experience?
Yes, but remote senior staff roles are harder to land without experience because employers expect you to operate independently from day one without in-person mentorship. Remote-first startups and early-stage technology companies are more open to candidates who can show self-directed project work, open-source contributions, or end-to-end portfolio projects that demonstrate senior-level judgment. Documented async collaboration skills and a clear record of shipping without close supervision open the door.
Do you need a degree for remote senior staff data scientist jobs?
Not always. Many remote employers care more about demonstrated expertise in machine learning, statistical modeling, and production data systems than about a specific credential. What consistently matters is a strong portfolio of real-world impact, fluency with the relevant technical stack, and evidence that you can operate at senior staff scope without an office environment to rely on.
Which industries hire the most remote senior staff data scientists?
The sectors hiring the most remote senior staff data scientists are Technology & Software, Artificial Intelligence, and Hospitality & Tourism, based on current remote listings on Migrate Mate as of November 2026. These industries have built distributed data organizations where senior staff scientists lead modeling, experimentation, and data strategy entirely asynchronously across geographies.
See All 23 Remote Senior Staff Data Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
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