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About This Role
Job Description
ACTIVE SECURITY CLEARANCE AT THE TOP SECRET LEVEL IS REQUIRED
We are seeking a Lead Data Scientist & Data Engineer to drive the modernization of an enterprise data management ecosystem containing hundreds of thousands of current and historical records for critical defense and intelligence customer missions. In this role, you will design, develop, and deploy scalable data engineering pipelines, advanced Natural Language Processing (NLP) solutions, semantic search frameworks, and automated document tagging capabilities. You will combine hands-on Python development with enterprise platform expertise (such as Databricks and Palantir Foundry) to transform massive volumes of structured and unstructured data into actionable operational intelligence.
The annual base salary range for this role is $229,000-$246,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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Required Skills
Data Engineering Pipelines: Hands-on experience designing, maintaining, and optimizing scalable ETL/ELT pipelines for structured and unstructured enterprise-scale data using Python, SQL, Apache Spark, and Databricks.
NLP & Machine Learning: Demonstrated ability to build, train, and deploy NLP pipelines for document summarization, text classification, clustering, automated tagging, and semantic search into production environments.
Data Quality & Profiling: Expertise conducting data-quality assessments, profiling, cleansing, validation, and anomaly detection to ensure high data integrity across large repositories.
Enterprise Platform Integration: Practical experience developing and deploying data pipelines and analytical workflows within enterprise data/AI platforms like Databricks, Palantir Foundry, or AWS/Azure cloud environments.
Agile & DevSecOps: Experience collaborating in Agile software development environments supporting automated testing, CI/CD, and DevSecOps practices.
Technical Communication & Mentorship: Ability to develop dynamic data visualizations/dashboards, communicate findings to diverse technical and leadership stakeholders, and provide technical guidance to junior engineers.
Education: Bachelor’s Degree in Data Analytics, Intelligence Studies, Computer Science, Finance/Economics, or a related discipline, PLUS 6+ years of specialized data analytics or financial intelligence experience OR High School Diploma / GED, PLUS 16+ years of hands-on intelligence analysis, financial tracking, and data discovery experience in lieu of a degree.
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Desired Skills
Palantir Foundry Ecosystem: Deep experience with Palantir Foundry, including Pipeline Builder, Code Repositories, custom transformations, and Ontology development.
Generative AI & LLMs: Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG architectures), vector databases, and embedding-based search techniques.
Advanced ML & Analytics: Hands-on experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and big data/NoSQL platforms (PySpark, Scala, R, MongoDB).
Business Intelligence & Visualization: Experience crafting executive reporting solutions using Tableau, Power BI, Qlik, or Python visualization libraries.
Federal & Mission Focus: Direct experience supporting Department of Defense (DoD), Intelligence Community (IC), or secure federal government cloud environments.
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About Nyla Technology Solutions
Nyla Technology Solutions delivers exceptional Artificial Intelligence (AI), Data Science, and Software Engineering services for the U.S. Government. Nyla embraces a forward-thinking and bold approach at every turn, earning us a solid reputation of technical trendsetters within the industry. We have a passion for developing solutions that have a quick and immediate impact on mission. Headquartered in Columbia, Maryland, our customers love how we tackle their most challenging problems and get things done.
If you have the unique experience and expertise we are seeking, along with the desire and determination to invest your time and energy as a part of Nyla’s team,
Taking Care of All of You
Nyla provides a top-of-market compensation and benefits package. And through our unique Nyla FLEX program, we custom tailor these benefits to best fit your lifestyle.
The Nyla FLEX benefit program is designed to offer you flexibility in the 3 biggest areas of your life: your pay, your leave, and your schedule.
PAY - Nyla starts with 4 weeks of Annual Leave plus 11 holidays and an additional day of Annual Leave for each year you’re at the company. You have the flexibility to cash out your annual leave hours, opt out of other Nyla benefits, and/or arrange for additional hours on contract* (over 40 hrs/week). There’s even an option to earn 1.3 times your hourly rate once you work over 1880 hours on contract!
LEAVE - Want to spend more time with the family? Want more time to travel the world? You can BUY additional annual leave for a total of 6 weeks of annual leave. That’s up to 240 hours of leave plus 11 holidays! That’s not even including paid anniversary leave!
SCHEDULE - Does the traditional 40-hour workweek no longer fit your lifestyle? With Nyla FLEX, you have the freedom to scale down to 30-32 hours while still enjoying the top-notch Nyla benefits you know and love. It's flexibility that works for you without compromising the perks!
WHAT ABOUT OTHER BENEFITS? Nyla’s health care (medical, dental, and vision) is 100% covered by the company. We provide 10% 401k matching - with full vesting day 1! Our Professional Development offers $5,000 per year to be used towards fees, tuition, or time off for your continued growth. We even have a student loan repayment program and we provide 8 hours of volunteering annually so you can support your community, making your world a better place.
To learn more about Nyla's culture and our exceptional benefit packages click here.
Nyla is an equal opportunity employer.
Salary Context
This $229K-$246K range is above the 75th percentile for Data Scientist roles in our dataset (median: $162K across 195 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 11,520 AI roles we're tracking, Data Scientist positions make up 4% of the market. At Nyla Technology Solutions, 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 $190,000 based on 1,564 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($237K) sits 25% above the category median. Disclosed range: $229K to $246K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Nyla Technology Solutions AI Hiring
Nyla Technology Solutions has 3 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer. Positions span Washington, DC, US, Annapolis Junction, MD, US. Compensation range: $184K - $246K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, 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 $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 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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