Staff Data Scientist

Company shown to members 🔒 · Remote · Location not stated

Location not stated5+ years required$160K–195K/yrPublished 4 August 2026Check carefully

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First recorded by Psst: 17 October 2026. Your first 3 jobs are free to apply to (the first right away, 2 more with your email). After that, the company and the apply link are for Psst members, from $4.99 for 7 days.

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The 20-second read

Experience
5+ years required
Where you can live
Location not stated
Skills and tools
python, docker, ci/cd
Degree or licence
Mentioned (bachelor's)

Read from the ad by Psst's rules. Check the full ad below before applying.

Job details

Where you can work
Location not stated
Employment type
Not stated by the employer
Advertised pay
$160K–195K/yr
Experience
5+ years required
Employer publication date
4 August 2026
First recorded by Psst
17 October 2026
Last checked at the source
10 November 2026

About the job

This is a fully remote opportunity with hybrid available to those local to Boston.

The company

The company is the decision-intelligence partner for the insurance industry, giving customers an advantage in how they make decisions by revealing risk others miss and translating it into stronger performance and real-world impact.   Our platform harnesses a vast industry data lake  –  tens of millions of policies and claims enriched with economic, health, geographic, and demographic signals  –  integrating cleanly with existing workflows to make complex risk clear, usable, and actionable.   Our customers include carriers, brokers, consultants, and specialized insurance organizations across the industry .    We are b acked by $56M in Series C funding  and  scaling fast  –  and  it's  an exciting time to join the team !

About the Role

We are looking for a Staff Data Scientist to lead complex modelling and analytical  projects of  broad and diverse scope. You will drive cross-product initiatives with minimal direction,  setting  the technical approach where problems are ambiguous and raising the bar for the entire data science team.

How you will make an impact

  • Leverage the best of modern deep learning & large language models with traditional data science techniques to create powerful hybrid models with real uplift.
  • Brainstorm, prototype, prove, deploy, and realize the value of your work in market quickly.
  • Everything you would expect on a world-class data science team solving world-class problems.  Big data.  Federated learning.  Unstructured data challenges.  Timeseries and sequence modelling.  A self-serve buffet of techniques from GLMs to XGBoost to Transformers.
  • Tell stories with your data.  Inspire trust in customers, stakeholders, and prospects by turning murky math into a powerful message that drives the bottom line.

Who you are and why we want to work with you

  • You like getting things over the line.  You have an insatiable desire to deliver value now and improve next.  MVP perfection is achieved not when there is nothing more to add, but when there is nothing left to take away.
  • You are not a software engineer, but you give them a run for their money.  You prefer Python to R and don’t understand why there is still a debate.  Jupyter is a necessary evil, and you’ve never met a command line that scared you away.
  • You still do a better job than Claude, and you’re skeptical of your friends who say they never code any more.
  • You love to take initiative and spearhead new projects, even if they are not well defined.
  • You build systems bigger than you. You contribute to open source, build packages your peers want to use, or design frameworks to elevate your team.  Reuse is a strategy, not a buzzword.

Skills needed to succeed

  • Bachelor's degree in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 5+ years of professional data science experience building predictive models
  • OR Master’s or Ph.D in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 3-5 years of professional data science experience building predictive models
  • Advanced proficiency with deep learning frameworks and the core Python data science ecosystem, and a deep understanding of modern AI architectures (e.g., Transformers, Neural Networks, LLMs) and related ML fields
  • Strong technical communication and collaboration skills, particularly communicating with nontechnical stakeholders and working collaboratively with engineering/product teams to meet project goals and timelines
  • MLOps and hands-on experience taking models from notebook to production — Experiment tracking, packaging, containerization (Docker), model serving and APIs, CI/CD, and pipeline orchestration
  • Monitoring models in production – tracking data and concept drift and performance degradation, with alerting
  • Strong peer leadership and ability to mentor junior DS on best practices and problem solving.  Experience setting and improving team standards.

Bonus Qualifications

  • Fluency with actuarial methods and working with actuaries is a plus
  • Familiarity with healthcare and medical data
  • Familiarity with underwriting and claims, or predicting long-tailed and/or rare events

What We Offer

  • A fun, team-oriented startup culture.
  • Generous stock options - we all get to own a piece of what we’re building.
  • Unlimited vacation days.
  • Flexible schedule that supports working from home.
  • Full benefits package includes medical, dental, vision, 401k, paid paternal leave, and more.
  • Ample opportunities to learn and take on new responsibilities.

We are an equal opportunity employer.

Salary Range: $160,000-195,000 base salary annually.

This role is also eligible for an annual performance bonus, equity grant, and a comprehensive benefits package.  In accordance with  the Massachusetts Pay Transparency Law, we are  providing  a good-faith salary range for this position at the time of posting. The actual salary offered will depend on the level at which the candidate is hired, as well as their experience, skills, qualifications, and location. Compensation may grow over time through merit-based increases, promotions, and company-wide adjustments.  If your salary expectations fall outside this range, we still encourage you to apply so we can have a conversation.

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