Interested in this Data Scientist role at BNSF Railway?
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About This Role
be part of a team that values safety, inclusion, and excellence
we are one of the largest U.S. railroads transporting the nation’s freight across 28 western states and 3 Canadian provinces. as a member of our team, you will play a role in supporting the movement of essential products and materials that help feed, clothe, supply, and power communities throughout America and the world.
bnsf \| tech: innovating and transforming the future of freight rail
bnsf \| tech is the technology division making BNSF the preeminent freight and mobility company in north america.
are you ready to drive change?
if you are passionate about making a difference and eager to advance your career in a dynamic and supportive environment, we want you on our team! join us in reshaping the future of freight rail and discover a fulfilling career where your contributions matter.
we are committed to a culture where all employees are included, belong, and have equal opportunity to achieve their full potential. Come make a difference with us!
learn more about BNSF and our Benefits
Job Location: Remote US
Anticipated Start Date: 08/03/2026
The US base salary range for this full\-time position is provided below:
Salary Range: $93,750\-$175,000
L3: $93,750 \- $125,000
L4: $123,750 \- $175,000
The range represents the amount bnsf \| tech reasonably expects to pay for the position based on the level, scope, and responsibilities of the role. Individual compensation and level of position offered is determined by the hiring location and additional factors including but not limited to job\-related skills, experience, and relevant education or training. In addition to base pay and bonus eligibility, BNSF offers a comprehensive benefits package.
This is a full\-time remote position. Employees may work from anywhere within the contiguous 48 states of the United States
Travel is up to 20%. Employees will be required to occasionally travel to our corporate headquarters in Fort Worth, TX for in person meetings. Travel expenses for business needs will be covered by BNSF
This position is open to candidates who are currently authorized to work in the United States. We are also open to sponsoring H\-1B transfers, TN nonimmigrant status, and STEM OPT candidates with at least 2 years of remaining eligibility.
Apply early as this job may be removed or filled prior to the closing date, which is approximately seven (7\) days after the posting date.
data \& ai: lead our charge into the future as an ai company by transforming our data assets into a real time enterprise.
*Key responsibilities may include:*
Work with cross\-functional teams to identify business problems and develop data\-driven solutions.
Apply data science skills to analyze large, complex datasets and identify meaningful patterns that lead to actionable insights and data\-driven solutions to business problems.
Develop and implement machine learning models to predict outcomes and improve processes.
Collaborate with stakeholders to understand their needs and provide actionable insights.
Create visualizations and reports to communicate findings effectively.
Maintain and update data pipelines to ensure data integrity and accuracy.
Stay current with industry trends and advancements in data science and machine learning.
Identify, extract, aggregate, and synthesize data using SQL and NoSQL databases, R, Python or other appropriate languages to enable analysis, model development, and solution deployment.
Drive moderate to complex data science, machine learning, traditional artificial intelligence, generative artificial intelligence or optimization projects, working with stakeholders to understand contextual problems quickly and define, analyze, and deliver solutions based on business objectives
Demonstrate operational excellence by monitoring, troubleshooting, and resolving production issues, including participating in a 24/7 on\-call rotation.
*The duties and responsibilities in this posting are representative categories to be used in deciding whether to apply for this position. This is not an exhaustive list of the position’s duties.*
At BNSF Railway, we encourage individuals from all backgrounds to apply, showcasing their skills, experiences and development. We provide resources and tools to help you reach your full potential, fostering a supportive and inclusive environment.
Basic Qualifications
- Minimum of 2 years experience building data science solutions or relevant experience
- Demonstrated understanding of statistical analysis and machine learning techniques.
- Experience with data visualization tools.
- Proficiency in programming languages such as Python, R, SQL, and familiarity with Java or Scala
- Experience with data science cloud platforms
Preferred Qualifications
- Bachelor's degree or higher in Operations Research, Computer Science, Industrial Engineering, or a related field
- Previous hands\-on experience with AI/Machine Learning frameworks and tools like TensorFlow, PyTorch, or scikit\-learn.
- Experience in Rail, Shipping, Airline, Logistics, Warehousing, Supply Chain, or other Transportation industries.
- Experience with geospatial python libraries
- Experience with open\-source libraries and frameworks.
- Experience working in an Agile environment (Scrum, Kanban, SAFe).
At BNSF, you will have access to a comprehensive and competitive benefits package including:
- An industry\-leading 401(k) and renowned Railroad Retirement program.
- A range of robust health care options for you and your dependents (including domestic partners), including medical, dental, vision, telemedicine, mental health, cancer support, and high\-quality care network options.
- Health care spending accounts (HSA) with employer contributions, as well as life and disability insurance, provided at no cost.
- Family benefits including parental, pediatric and family building support, adoption and surrogacy reimbursement, and dependent care spending account (with employer match).
- Access to discounts on travel, gym memberships, counseling services and wellness support.
- Annual bonus (Incentive Compensation Program)
- Generous leave / time off policies.
- For more information, visit Benefits.
Federal authority requires BNSF employees, whose work requires unescorted access to secure areas of port facilities, to obtain a TWIC. More information is available at https://www.tsa.gov/for\-industry/twic
BNSF Railway is an Equal Opportunity Employer, all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
Salary Context
This $93K-$175K range is below 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 BNSF Railway, 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. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($134K) sits 30% below the category median. Disclosed range: $93K to $175K.
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.
BNSF Railway AI Hiring
BNSF Railway has 1 open AI role right now. They're hiring across Data Scientist. Based in Remote, US. Compensation range: $175K - $175K.
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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