Senior Data Scientist

$200K - $275K Saint George, UT, US Senior Data Scientist

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Skills & Technologies

EmbeddingsPostalPython

About This Role

AI job market dashboard showing open roles by category

St. George, UT Full-time Posted 2026-10-13

Zonos is the AI operating system for cross-border trade, powering everything from checkout to customs clearance for more than 50,000 ecommerce merchants and 70+ postal operators across 200+ countries. We help businesses grow globally by removing the complexity of international commerce—calculating, collecting, and guaranteeing duties, taxes, and fees at checkout so shoppers see the true total cost upfront, eliminating surprise charges at delivery and the burden of managing country-specific tax requirements. Beyond ecommerce, Zonos supports carriers, postal operators, marketplaces, and customs agencies with AI-driven tools that infer and validate key customs data, including HS codes, country of origin, and customs value, alongside licensed customs brokerage services that ensure goods move compliantly and efficiently across borders.

Overview

Behind almost every part of that is a data problem. Inferring an HS code from a messy product title, estimating customs value, deciding when an answer is confident enough to guarantee, spotting the shipments that need a human, and pricing risk across 200+ countries all have real financial and regulatory consequences.

We're hiring a data scientist who solves problems and ships the solution. Sometimes that's a fine-tuned LLM. Sometimes it's a Bayesian model, a well-designed experiment, an optimization, a simulation, or a 30-line rule that beats everything else. We want someone with the whole toolbelt and the judgment to pick the right tool. Cleverness for its own sake doesn't interest us.

You'll report directly to our Chief Data Scientist and work side by side with engineering, taking problems from "fuzzy and important" to something running in production that customers rely on.

How we work

Zonos doesn't have product managers. At the senior level, you talk to customers and internal teams directly, understand the problem, decide what's worth solving and how, and ship it. Part of the job is judgment: pushing back, proposing a simpler approach, or saying the data doesn't support the decision. Disagreements get resolved quickly and in writing, with clear owners.

Life in St. George UT

This role is on-site at our headquarters in St. George, Utah, where our team enjoys Southern Utah's 300 days of sunshine each year. Snow Canyon State Park is minutes away, Zion National Park is about an hour's drive, and Las Vegas is about two. Relocation assistance is available for candidates moving here.

What you'll do

  • Own data problems at the heart of the product, such as classification, valuation, risk, and compliance. Choose the approach, whether that's statistical modeling, classical ML, deep learning and LLMs, optimization, or a simple rule.
  • Work with messy, multilingual product and shipment data. Figure out what it actually says before modeling anything.
  • Quantify uncertainty and make it useful. Decide when we're confident enough to act, when to route work to a human, and what each error costs.
  • Design the evaluations, experiments, and analyses that tell us whether something actually worked, and hold the line when it didn't.
  • Write production-quality Python and SQL, then ship, monitor, and iterate on what you build.
  • Join the on-call rotation and debug in production, including the subtle failures that only show up on real traffic.
  • Bring rigor to product and business decisions beyond your own projects.

You might be a great fit if you...

  • Reach for the right tool, not the newest one. You can explain why you chose a GLM over a transformer, or a heuristic over both, and tell us how it played out.
  • Own the full loop. You've framed a problem, built the solution, shipped it, and stayed with it after launch.
  • Can point to impact. You've shipped work that moved a real metric, and you can tell us which one and how you measured it.
  • Write code engineers are happy to merge. You explore in notebooks, and you ship clean, tested code.
  • Lead with product judgment. You ask "should we solve this?" before "how do we solve this?"
  • Want to live and work in sunny St. George, Utah, with a real work-life balance.
  • You also bring: + 5+ years of hands-on data science work with a Bachelor's degree, or 3+ years with a Master's or PhD, including things you built that ran in production. + Real depth in statistics: inference, experimental design, and uncertainty. You understand what the numbers mean, not just how to produce them. + Practical experience with ML and LLMs/NLP, including fine-tuning, embeddings, evaluation, and text classification at scale. + Strong Python and SQL.
  • Nice to have: optimization or operations research, causal inference, forecasting, Bayesian methods, serving models on GPUs, and experience with trade, customs, logistics, ecommerce, or payments data.

What we offer

  • Compensation: $200,000–$275,000 annual base salary, depending on experience and demonstrated impact. If your compensation expectations fall outside this range, we'd still love to hear from you. We're focused on finding the right person and are willing to be flexible for exceptional talent.
  • Relocation assistance is available for candidates relocating to St. George, Utah.
  • Medical, Dental, Vision, & Life - we pay 100% of the employee premium!
  • Paid parental leave and other life event leave
  • 401k retirement plan with generous company match
  • 4 weeks of vacation, plus sick and other paid time off. Take some time to relax!
  • Employee Assistance Program
  • 1 month paid time off at 5 year anniversary
  • Office stocked with snacks and drinks
  • Weekly company lunch

Ready to Join the Team?

Become a Zonut and help us create trust in global trade. We're building something meaningful—a company that puts people first and makes cross-border commerce accessible to everyone. If you're passionate about solving complex challenges with cutting-edge technology, we'd love to meet you.

Salary Context

This $200K-$275K range is above the 75th percentile for Data Scientist roles in our dataset (median: $161K across 138 roles with salary data).

View full Data Scientist salary data →

Role Details

Company Zonos
Title Senior Data Scientist
Location Saint George, UT, US
Category Data Scientist
Experience Senior
Salary $200K - $275K
Remote No

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 9,079 AI roles we're tracking, Data Scientist positions make up 4% of the market. At Zonos, 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

Embeddings (2% of roles) Postal Python (18% of roles)

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 $190,000 based on 1,503 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($237K) sits 25% above the category median. Disclosed range: $200K to $275K.

Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.

Zonos AI Hiring

Zonos has 1 open AI role right now. They're hiring across Data Scientist. Based in Saint George, UT, US. Compensation range: $275K - $275K.

Location Context

Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).

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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.

The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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

Based on 1,503 roles with disclosed compensation, the median salary for Data Scientist positions is $190,000. Actual compensation varies by seniority, location, and company stage.
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.
About 6% of the 9,079 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Zonos is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from Data Scientist positions include Senior Data Scientist, ML Engineer, AI Product Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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