Pay
In line with similar jobs
$127K–$224K against $118K–$194K, the middle half of what similar US postings state.
From 3,761 postings in the last year. Stated ranges, not salaries paid.
Staff Data Scientist
- Pay
$127,000–224,000/year · BaseAnnual period assumed — pay source
#LI-Remote #LI-TL1 The US national base salary range for this full-time position is $127,000 - $224,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only and do not include applicable bonus, equity, or benefits.
Read the full posting- Work setting
Remote — work setting source
Listed location: Remote US
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingWe're looking for a Staff Data Scientist to own the product modeling roadmap and contribute to marketing measurement.
Own the end-to-end lifecycle of ML models powering product experiences, coverage recommenders, user-to-channel routing, and agent assignment logic
Own the end-to-end lifecycle of ML models for product experiences
Engineer features, prototype experiments, and ship model improvements to production
Define with engineering and PMs how model scores are used in real-time product surfaces
From the employer’s posting
We're looking for a Staff Data Scientist to own the product modeling roadmap and contribute to marketing measurement. You'll design, build, and deploy production ML models, partnering closely with PMs to scope and prioritize. The right candidate defines what to model before anyone asks, stress-tests their own assumptions, and communicates uncertainty in terms stakeholders can act on.
Own the end-to-end lifecycle of ML models powering product experiences, coverage recommenders, user-to-channel routing, and agent assignment logic
Own the end-to-end lifecycle of ML models powering product experiences
Engineer features, prototype experiments, and ship iterative model improvements to production
Work with engineering and PMs to define how model scores are consumed in real-time product surfaces
What you’ll bring
All qualificationsCore experience
- 5+ years in data science or ML
- Strong supervised learning and recommendation systems experience with shipped production models
- Proficiency in Python (pymc, scikit-learn, XGBoost/LightGBM) and SQL
- Hands-on Bayesian experience: prior elicitation, posterior inference, experiment design
- Experience deploying production models in consumer-facing products
Qualification wording
5+ years in data science or ML at established firms or high-growth tech
Strong command of supervised learning and recommendation systems; you've shipped production models, not just notebooks
Proficiency in Python (pymc, scikit-learn, XGBoost/LightGBM) and SQL
Hands-on Bayesian experience: prior elicitation, posterior inference, and experiment design
Experience deploying production models integrated with consumer-facing products
About Ethos Life
Ethos (Nasdaq: $LIFE) is a leading life insurance technology company on a mission to protect families by democratizing access to life insurance and empowering agents at scale.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 3 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 4, 20263 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 7, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 3
Early. Similar jobs usually come down between day 7 and day 57.
At Ethos Life, jobs usually come down by about day 40.
From 10,552 similar postings that came down, and 8 of Ethos Life’s. Coming down is not always a hire.
Ethos Life is hiring
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- dbt
- MLflow
- LightGBM
- scikit-learn
- XGBoost
Where the posting names them
- Strong command of supervised learning and recommendation systems; you've shipped production models, not just notebooks - Proficiency in Python (pymc, scikit-learn, XGBoost/LightGBM) and SQL - Hands-on Bayesian experience: prior elicitation, posterior inference, and experiment design
- Experience in insurtech, fintech, or other regulated industries - dbt or data pipeline experience - MLflow, feature stores, or other ML infrastructure tooling
- dbt or data pipeline experience - MLflow, feature stores, or other ML infrastructure tooling - Gets in the weeds without losing the bigger picture
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
About Ethos
Ethos (Nasdaq: $LIFE) is a leading life insurance technology company on a mission to protect families by democratizing access to life insurance and empowering agents at scale. With its robust three-sided technology platform, Ethos is transforming the life insurance experience for consumers, agents, and carriers alike. Ethos offers instant, accessible products and a seamless online process that requires no medical exams and just a few health questions; it eliminates traditional barriers, making it easier than ever for everyone to protect their families. Ethos is redefining how life insurance is bought, sold, and underwritten.
About the role
We're looking for a Staff Data Scientist to own the product modeling roadmap and contribute to marketing measurement. You'll design, build, and deploy production ML models, partnering closely with PMs to scope and prioritize. The right candidate defines what to model before anyone asks, stress-tests their own assumptions, and communicates uncertainty in terms stakeholders can act on.
Duties and Responsibilities:
- Own the end-to-end lifecycle of ML models powering product experiences, coverage recommenders, user-to-channel routing, and agent assignment logic
- Engineer features, prototype experiments, and ship iterative model improvements to production
- Work with engineering and PMs to define how model scores are consumed in real-time product surfaces
Qualifications and Skills:
- 5+ years in data science or ML at established firms or high-growth tech
- Strong command of supervised learning and recommendation systems; you've shipped production models, not just notebooks
- Proficiency in Python (pymc, scikit-learn, XGBoost/LightGBM) and SQL
- Hands-on Bayesian experience: prior elicitation, posterior inference, and experiment design
- Experience deploying production models integrated with consumer-facing products
- Strong communication skills; able to translate model behavior and uncertainty into stakeholder recommendations
- Bias toward ownership; you identify what needs to be built before anyone files a ticket
- Recommender systems or personalization at scale
- Causal inference: diff-in-diff, uplift modeling, instrumental variables
- Marketing mix modeling, media attribution, or incrementality measurement
- Experience in insurtech, fintech, or other regulated industries
- dbt or data pipeline experience
- MLflow, feature stores, or other ML infrastructure tooling
- Gets in the weeds without losing the bigger picture
- Knows the tradeoffs between simple heuristics and ML solutions and picks the right tool for the job
- Aligns model performance metrics to business objectives and combines multiple models into a coherent solution
- Raises the team's data science bar through code review, documentation, and mentorship
#LI-Remote #LI-TL1
The US national base salary range for this full-time position is $127,000 - $224,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Please note that the compensation details listed in US role postings reflect the base salary only and do not include applicable bonus, equity, or benefits.
You can find further details of our US benefits at https://www.ethoslife.com/careers/
Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. At Ethos we are dedicated to building a diverse, inclusive and authentic workplace.
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Pursuant to the SF Fair Chance Ordinance, we will consider employment for qualified applicants with arrests and conviction records.
To learn more about what information we collect and how it may be used, please refer to our California Candidate Privacy Notice.
Recruitment Notice: Please be aware of recruitment scams. All legitimate communication from our team will only come from email addresses ending in @ethos.com or @getethos.com.
We will never ask for payment, banking details, or sensitive personal information during the hiring process. If you are contacted by someone claiming to represent us from a different email address, please treat it as fraudulent.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
#LI-Remote #LI-TL1 The US national base salary range for this full-time position is $127,000 - $224,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only and do not include applicable bonus, equity, or benefits.
- Location & working pattern
Remote US
- Raises the team's data science bar through code review, documentation, and mentorship #LI-Remote #LI-TL1 The US national base salary range for this full-time position is $127,000 - $224,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.