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About This Role
Lumen is the trusted network for the AI‑powered world, connecting people, data, and applications through our expansive fiber network and connected ecosystem. We enable secure, high‑performance connectivity across cloud, edge, and AI workloads for enterprises, governments, and communities.
At Lumen, you’ll work on infrastructure customers rely on today and build for what’s next, where performance, security, and resilience matter.
This is a high accountability environment where bold ideas drive real innovation for our customers, partners, and industry. The work is challenging, expectations are clear, and trust is built into how we operate. If you’re ready to take ownership, deliver meaningful impact, and help shape the future of AI‑ready connectivity, join us today.
The Role
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As Lumen continues this journey, Corporate Finance is playing a critical role in shaping the future through data and AI. We are seeking a Senior Data Scientist who is excited by the opportunity to turn information into impact. In this role, you’ll leverage Databricks, Generative AI, and advanced analytics to create scalable solutions that empower smarter decision\-making. You’ll help expand self\-service insights, automate finance processes, and uncover opportunities hidden within complex datasets. More than building models, you’ll help write the next chapter of Lumen’s transformation—where data becomes a strategic advantage and innovation drives meaningful business outcomes.
Location
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This is a work from home position from within the US.
The Main Responsibilities
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- Build and enhance Databricks\-based AI and analytics solutions that improve how Finance teams access and use insights.
- Develop scalable data pipelines, workflows, and reporting solutions using Databricks, Data Factory, SQL, Python, and Power BI.
- Apply statistical, forecasting, and machine learning techniques to solve business problems and strengthen decision support.
- Automate manual processes, improve data quality, and strengthen the performance and reliability of analytics applications.
- Partner across Finance, FP\&A, Data Science, and IT to turn business needs into practical solutions and actionable insights.
- Contribute to high\-impact initiatives that advance how data and AI are used across Finance.
What We Look For in a Candidate
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- 3–5 years of experience in data science, data engineering, analytics, or a related role
- Strong Python and SQL skills
- Experience with Databricks, PySpark, or Spark\-based processing
- Experience building data pipelines and working with large, complex datasets
- Strong analytical, problem\-solving, and communication skills
Preferred Qualifications
- Experience with forecasting, predictive modeling, statistical analysis, or machine learning techniques
- Experience with Generative AI or LLM\-based applications
- Experience with Power BI or similar visualization tools
- Exposure to financial data, FP\&A, or enterprise reporting
Compensation
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This information reflects the anticipated base salary range for this position based on current national data. Minimums and maximums may vary based on location. Individual pay is based on skills, experience and other relevant factors.
Location Based Pay Ranges
$84,629 \- $112,838 in these states: AL AR AZ FL GA IA ID IN KS KY LA ME MO MS MT ND NE NM OH OK PA SC SD TN UT VT WI WV WY
$88,860 \- $118,480 in these states: CO HI MI MN NC NH NV OR RI
$93,092 \- $124,122 in these states: AK CA CT DC DE IL MA MD NJ NY TX VA WA
Lumen offers a comprehensive package featuring a broad range of Health, Life, Voluntary Lifestyle benefits and other perks that enhance your physical, mental, emotional and financial wellbeing. We're able to answer any additional questions you may have about our bonus structure (short\-term incentives, long\-term incentives and/or sales compensation) as you move through the selection process.
Learn more about Lumen's:
- Benefits
- Bonus Structure
\#LI\-Remote
Requisition \#: 342510
Life at Lumen
Life at Lumen is human and connected, even in a fast moving, AI‑focused organization. We set clear expectations and trust people to meet them. With real support and shared accountability, teams collaborate better, move faster, and deliver meaningful outcomes.
Our Lumen 8 behaviors guide how we interact, make decisions, and work together, shaping a culture built to perform and win.
To learn more about Life at Lumen and how we live the Lumen 8, please visit:
https://jobs.lumen.com/global/en/life\-at\-lumen
Background Screening
If you are selected for a position, there will be a background screen, which may include checks for criminal records and/or motor vehicle reports and/or drug screening, depending on the position requirements. For more information on these checks, please refer to the Post Offer section of our FAQ page. Job\-related concerns identified during the background screening may disqualify you from the new position or your current role. Background results will be evaluated on a case\-by\-case basis.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Equal Employment Opportunities
We are committed to providing equal employment opportunities to all persons regardless of race, color, ancestry, citizenship, national origin, religion, veteran status, disability, genetic characteristic or information, age, gender, sexual orientation, gender identity, gender expression, marital status, family status, pregnancy, or other legally protected status (collectively, “protected statuses”). We do not tolerate unlawful discrimination in any employment decisions, including recruiting, hiring, compensation, promotion, benefits, discipline, termination, job assignments or training.
Privacy Notice
Lumen is committed to protecting the privacy and security of personal information collected during the recruitment and hiring process. Our Applicant Privacy Notice explains how we collect, use, disclose, and protect applicant information, as well as how individuals may request access to or deletion of their personal data.
To review Lumen’s Global Employment Applicant and Talent Community Privacy Notice, please visit:
https://jobs.lumen.com/global/en/privacy\-notice
Disclaimer
The job responsibilities described above indicate the general nature and level of work performed by employees within this classification. It is not intended to include a comprehensive inventory of all duties and responsibilities for this job. Job duties and responsibilities are subject to change based on evolving business needs and conditions.
In any materials you submit, you may redact or remove age\-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.
Please be advised that Lumen does not require any form of payment from job applicants during the recruitment process. All legitimate job openings will be posted on our official website or communicated through official company email addresses. If you encounter any job offers that request payment in exchange for employment at Lumen, they are not for employment with us, but may relate to another company with a similar name.
Salary Context
This $84K-$124K range is in the lower quartile 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 Lumen, 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 ($104K) sits 46% below the category median. Disclosed range: $84K to $124K.
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.
Lumen AI Hiring
Lumen has 2 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Based in Remote, US. Compensation range: $124K - $256K.
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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