Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Applied Scientist, AI/ML
Reads like a ML Engineer role: putting models into production.
- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
Employment terms need review — employment source
Employment type Full-Time or Part-Time
Read the full posting
What you’ll work on
Full postingFrame problems and run research and experiments on them
Design and analyze experiments and combine predictive modeling with causal inference
Develop multimodal models and foundation models on medical event sequences
Build agents that work with complex data and workflows
Iterate on models after they run in production
From the employer’s posting
you’ll carry the work from initial framing and research through experimentation, model development
That might mean designing and analyzing experiments; combining predictive modeling with causal inference
developing multimodal models that combine images, text, and structured data; training foundation models on sequences of medical events
or building agents that work with complex data and workflows
continued iteration in production
What you’ll bring
All qualificationsCore experience
- Deep expertise in machine learning, statistics, econometrics, or causal inference
- Strong grounding in math and statistics behind ML, inference, and experimental design
- Fluency in Python and its data and ML ecosystem
- Degree in computer science, economics, statistics, mathematics, physics, engineering, or related quantitative field
Qualification wording
Deep expertise in at least one relevant area—such as machine learning, statistics, econometrics, or causal inference
Strong command of the mathematical and statistical foundations behind machine learning, statistical inference, and experimental design.
Fluency in Python and its data and ML ecosystem
A degree in computer science, economics, statistics, mathematics, physics, engineering, or a related quantitative field.
Education & alternatives
We work in areas such as algorithmic pricing, claims management, underwriting, and predictive health. You’ll build on a shared technology base that improves with each new application, while choosing—and when needed, developing—methods to fit the problem. That might mean designing and analyzing experiments; combining predictive modeling with causal inference; developing multimodal models that combine images, text, and structured data; training foundation models on sequences of medical events; or building agents that work with complex data and workflows. The resulting systems run in production at organizations serving millions of people, informing and automating critical business decisions that affect billions of dollars. You’ll have unusual autonomy over how they’re designed and built. There is no single path into this role. Our applied scientists come from AI research, economics, statistics, computer science, and other quantitative fields. The team brings together colleagues with PhDs as well as those with master’s and bachelor’s degrees. What they share is exceptional quantitative judgment, the ability to learn quickly, and the drive to turn ideas into systems that deliver measurable real-world impact. You may be a strong fit if you have:
Nice to have: - An advanced degree (MS/PhD) in one of the fields above. - Hands-on experience training, adapting, or evaluating deep learning and foundation models, or the curiosity and technical foundations to get there quickly.
Benefits in the posting
Full benefits wording- You’ll join an intellectually curious, interdisciplinary team that thrives on solving difficult problems and developing novel solutions that work in practice. We care deeply about our customers and build thoughtful products that deliver meaningful impact. You'll work alongside colleagues who take one another’s ideas seriously, challenge each other thoughtfully, and are eager to learn across disciplines. We offer a generous compensation package that includes a base salary, bonus, and equity, along with additional location-based benefits.
From the employer’s posting.
About Quantco-
We build production systems that enable organizations to make and execute better decisions.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 31, 202665 days ago
- Recorded sightings
- 49
- Last seen by us
- Nov 3, 2026
- Employer says posted
- Aug 29, 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 65
Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
Quantco- is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee 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
- LightGBM
- pandas
- Polars
- PyTorch
- scikit-learn
- XGBoost
Where the posting names them
- Strong command of the mathematical and statistical foundations behind machine learning, statistical inference, and experimental design. - Fluency in Python and its data and ML ecosystem (e.g., pandas/Polars, scikit-learn, PyTorch/JAX, XGBoost/LightGBM). - A degree in computer science, economics, statistics, mathematics, physics, engineering, or a related quantitative field.
Your next step
Complete your application on jobs.lever.co. The employer’s form will show what is required.
Applying through Lever
- No account needed: one form, and Lever reads your resume into the profile recruiters search.
Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
As an Applied Scientist, AI/ML at QuantCo, you'll bring together advances in AI with rigorous economic and quantitative thinking to build models and systems that power high-stakes decisions across industries. Those systems tackle some of the hardest, most consequential problems our customers face, and you’ll carry the work from initial framing and research through experimentation, model development, and continued iteration in production.
We work in areas such as algorithmic pricing, claims management, underwriting, and predictive health. You’ll build on a shared technology base that improves with each new application, while choosing—and when needed, developing—methods to fit the problem. That might mean designing and analyzing experiments; combining predictive modeling with causal inference; developing multimodal models that combine images, text, and structured data; training foundation models on sequences of medical events; or building agents that work with complex data and workflows. The resulting systems run in production at organizations serving millions of people, informing and automating critical business decisions that affect billions of dollars. You’ll have unusual autonomy over how they’re designed and built.
There is no single path into this role. Our applied scientists come from AI research, economics, statistics, computer science, and other quantitative fields. The team brings together colleagues with PhDs as well as those with master’s and bachelor’s degrees. What they share is exceptional quantitative judgment, the ability to learn quickly, and the drive to turn ideas into systems that deliver measurable real-world impact.
You may be a strong fit if you have:
-
Deep expertise in at least one relevant area—such as machine learning, statistics, econometrics, or causal inference—and an interest in learning and working beyond it.
-
Strong command of the mathematical and statistical foundations behind machine learning, statistical inference, and experimental design.
-
Fluency in Python and its data and ML ecosystem (e.g., pandas/Polars, scikit-learn, PyTorch/JAX, XGBoost/LightGBM).
-
A degree in computer science, economics, statistics, mathematics, physics, engineering, or a related quantitative field.
Nice to have:
-
An advanced degree (MS/PhD) in one of the fields above.
-
Hands-on experience training, adapting, or evaluating deep learning and foundation models, or the curiosity and technical foundations to get there quickly.
What we offer:
You’ll join an intellectually curious, interdisciplinary team that thrives on solving difficult problems and developing novel solutions that work in practice. We care deeply about our customers and build thoughtful products that deliver meaningful impact. You'll work alongside colleagues who take one another’s ideas seriously, challenge each other thoughtfully, and are eager to learn across disciplines. We offer a generous compensation package that includes a base salary, bonus, and equity, along with additional location-based benefits.
About QuantCo
QuantCo is an applied AI company. We build production systems that enable organizations to make and execute better decisions. Combining modern AI with causal inference, economic modeling, and optimization, we improve outcomes in high-stakes areas like pricing, underwriting, claims, and forecasting. Our customers include some of the largest insurers, financial institutions, retailers, and healthcare organizations in the US and Europe.
We bring together 250+ AI researchers, economists, data scientists, and software engineers to close the gap between what AI can predict and what organizations should do. Founded by four Harvard and Stanford PhDs and headquartered in Boston, we have offices in Berlin, Cologne, Karlsruhe, London, Munich, San Francisco, and Zurich.
QuantCo does not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
Employment type
Full-Time or Part-Time
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
USA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.