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About This Role
About the team
Symetra's AI Enablement team is a fast\-growing team of builders inside our Data Analytics organization. Our goal is to accelerate AI adoption across the company in two ways: by building shared platforms, tooling, and patterns that let other teams effectively integrate AI into their workflows, and by shipping AI\-powered applications for the most important use cases.
We work in small, cross\-functional teams, build with the people who use what we make, and move fast. Our first product in production, docstream, is an AI\-powered document\-processing platform that currently supports several of Symetra's back\-end operational processes. We plan to continue to iterate on docstream and to build out other products using the same modular architecture, integrating third\-party products where it makes sense.
About the role
As a Lead Data Scientist, you'll own the AI and machine learning behind our products: framing the problems, choosing the approaches, and building and evaluating the models (classic ML and LLM\-based) that make our products work. You'll set the standard for how we do data science on the team, mentor other data scientists, and partner closely with the engineers and stakeholders building alongside you.
What you will do
- Frame business and product questions, and define how we'll measure success.
- Build and evaluate models that power our AI products, from classic ML to LLM\-based systems (RAG, agents).
- Own projects end to end, and recommend where to focus next.
- Set the standard for evaluations, guardrails, and prompting across our LLM systems, and champion data science best practices.
Mentor data scientists and partner closely with the engineers building our products.
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Who You Are
- An experienced data scientist (typically 8\+ years) who has owned modeling work end to end.
- Deep expertise in statistics, machine learning, and model development.
- Strong with modern AI: LLMs, RAG, agents, prompt engineering, evaluation, and guardrails.
- Python and SQL, and a track record of getting models into production.
Use AI coding agents effectively in your day\-to\-day work, with the judgment to know when to use them and when not to.
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Nice to Haves
- Building and scaling LLM\-powered systems in production.
- Document understanding, NLP, or other unstructured\-data experience.
- A track record of mentoring data scientists and leading technical direction.
Why Work at Symetra
Here’s what some of our employees have to say about why they work at Symetra:
*“Symetra is a great place if you are looking for the opportunity to contribute, to grow, to be seen and valued.” Vernell K. – Auditor“We're big enough to make an impact on the country, but small enough to care and know who you are and what you're contributing to the organization. All new ideas are welcome!” Stephanie F. – VP Customer Service \& Operations*What we offer you**
Benefits and Perks
We don’t take a “one\-size\-fits\-all” approach when it comes to our employees. Our programs are designed to make your life better both at work and at home.
- Flexible full\-time or hybrid telecommuting arrangements
- Plan for your future with our 401(k) plan and take advantage of immediate vesting and company matching up to 6%
- Paid time away including vacation and sick time, flex days and ten paid holidays
- Give back to your community and double your impact through our company matching
Want more details? Check out our Symetra Benefits Overview
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Compensation
Salary Range: $128,700 \- $214,600 plus eligibility for annual bonus program
Please review Symetra’s Remote Network Minimum Requirements:
As a remote\-first organization committed to providing a positive experience for both employees and customers, Symetra has the following standards for employees’ internet connection:
- Minimum Internet Speed: 100 Mbps download and 20 Mbps upload, in alignment with the FCC's definition of "broadband."
- Internet Type: Fiber, Cable (e.g., Comcast, Spectrum), or DSL.
- Not Permissible: Satellite (e.g., Starlink), cellular broadband (hotspot or otherwise), any other wireless technology, or wired dial\-up.
When applying to jobs at Symetra you’ll be asked to test your internet speed and confirm that your internet connection meets or exceeds Symetra’s standard as outlined above.
Identity Verification
Symetra is committed to fair and secure hiring practices. For all roles, candidates will be required (after the initial phone screen) to be on video for all interviews. Symetra will take affirmative steps at key points in the process to verify that a candidate is not seeking employment fraudulently, e.g. through use of a false identity.
Failure to comply with verification procedures may result in:
- Disqualification from the recruitment process
- Withdrawal of a job offer
- Termination of employment and other criminal and/or civil remedies, if fraud is discovered
We empower inclusion
At Symetra, we aspire to be the most inclusive insurance company in the country. We’re building a place where every employee feels valued, respected, and has opportunities to contribute.
Inclusion is about recognizing our assumptions, considering multiple perspective, and removing barriers. We accept and celebrate diverse experiences, identities, and perspectives, because lifting each other up fuels thought and builds a stronger, more innovative company. We invite you to learn more about our efforts here .
Creating a world where more people have access to financial freedom
Symetra is a national financial services company dedicated to helping people achieve their financial goals and feel confident about the future. In our daily work, we’re guided by the principles of Value, Transparency and Sustainability. This means we provide products and services people need at a competitive price, we communicate clearly and openly so people understand what they’re buying, and we design products—and operate our company—to stand the test of time. We’re committed to showing up for our communities, lifting up our employees, and standing up for diversity, equity and inclusion (DEI). Join our team and help us create a world where more people have access to financial freedom.
For more information about our careers visit https://symetra.eightfold.ai/careers
Work Authorization
Employer work visa sponsorship and support are not provided for this role. Applicants must be currently authorized to work in the United States at hire and must maintain authorization to work in the United States throughout their employment with our company.
Salary Context
This $128K-$214K range is above the median for Data Scientist roles in our dataset (median: $155K across 226 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Symetra, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 463 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($171K) sits 11% below the category median. Disclosed range: $128K to $214K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Symetra AI Hiring
Symetra has 3 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Bellevue, WA, US, US. Compensation range: $161K - $214K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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