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About This Role
Position: Senior Data Scientist
Location: Aurora, CO
Clearance: TS/SCI with CI Polygraph
Support Emerging Mission Needs and Help Shape DeNOVO’s Data Science Capability
DeNOVO Solutions is seeking a Senior Data Scientist to help develop, refine, and strengthen our data science and mission\-focused technical capabilities. This is a unique opportunity for a senior\-level data scientist with a strong background in applied machine learning, data engineering, software development, secure deployment environments, and technical leadership. The ideal candidate will be comfortable working across research, development, architecture, deployment, and stakeholder engagement while helping shape practical AI/ML solutions for emerging mission needs.
Why You’ll Love This Role:
- Help develop and refine DeNOVO’s broader data science capability
- Work closely with DeNOVO’s CEO in a highly visible role focused on capability growth and technical direction
- Apply advanced data science, machine learning, data engineering, and software development experience to emerging mission needs
- Help shape practical AI/ML solutions that support mission\-focused opportunities
- Work in a hands\-on role that blends research, solution design, implementation, deployment, and stakeholder collaboration
A Day in the Life:
- Help develop and refine DeNOVO’s data science capability
- Research, build, evaluate, and deploy machine learning and AI\-enabled applications
- Design and implement data science solutions that align with user needs, mission goals, and technical objectives
- Communicate with technical and non\-technical stakeholders to understand requirements, data landscapes, and solution goals
- Provide technical recommendations to ensure data science and AI/ML solutions are practical, scalable, and aligned to stakeholder needs
- Develop and support machine learning, generative AI, and LLM\-based applications where applicable
- Support semantic search, summarization, text extraction, classification, embedding analysis, and natural language processing use cases
- Build scalable data pipelines and support data engineering workflows
- Develop backend services, APIs, microservices, and data\-driven applications
- Support deployment of software and data science applications in commercial cloud and secure environments
- Use containerization and orchestration technologies to package, deploy, and manage software components
- Support MLOps, DevOps, and GitOps practices to improve repeatability, deployment efficiency, and lifecycle management
- Develop visualizations, dashboards, and analytical tools to help communicate insights and recommendations
- Collaborate with leadership, engineers, and stakeholders to identify opportunities for data science, automation, and AI/ML capability growth
- Provide technical leadership, mentoring, and guidance to other technical contributors as needed
- Create documentation, technical recommendations, and capability\-development materials to support long\-term growth
What You Bring to the Table:
- Senior\-level experience in data science, data engineering, machine learning, and software development
- Experience researching, building, evaluating, and deploying machine learning and AI\-enabled applications
- Strong background with applied machine learning, including supervised and unsupervised learning approaches
- Experience with generative AI, large language models, RAG, semantic search, summarization, text extraction, and NLP\-related use cases
- Experience building scalable data pipelines and supporting data engineering workflows
- Experience developing APIs, microservices, backend services, and data\-driven applications
- Experience deploying software or data science applications in commercial cloud and secure environments
- Experience with containerization, orchestration, and modern deployment practices
- Familiarity with MLOps, DevOps, GitOps, Agile/Scrum, and modern software development methodologies
- Strong communication skills with the ability to work with technical and non\-technical stakeholders
- Ability to provide technical leadership, mentorship, and solution guidance in a hands\-on environment
What You Need:
- Experience: 15 years of experience in data science, data engineering, machine learning, software development, or a related technical discipline
- Education: Bachelor’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field preferred
- Clearance: An active TS/SCI with CI Polygraph
Salary Range: $150,000\.00 \- $190,000\.00 (Commensurate with experience)
Note: The above salary range is a guideline and represents a broad spectrum of potential compensation. We recognize that a candidate's unique experience and qualifications may justify compensation beyond this range. Therefore, we remain open to considering higher salary offers for exceptionally qualified candidates.
About Us: DeNOVO Solutions. We make improving the competitive position of our customer paramount in importance and work collaboratively to ensure the best service possible. DeNOVO Solutions provides cleared personnel and cost competitive solutions to our customers. We strive to be the leader amongst small businesses in the Intelligence Community and provide personnel with talent \& skills equal to the larger companies.
Join Our Team! DeNOVO Solutions, LLC, a Minority Owned\-Service Disabled Veteran Owned Small Business (MO/SDVOSB) dedicated to providing the best technical and professional services throughout the Intelligence Community (IC). We offer the following as part of our benefits package to all of our full\-time employees:
- Medical, Dental, and Vision Premiums 100% Employer Paid for you and your legal dependents or plus up, cost split plan.
- DeNOVO Paid Health Reimbursement Account (HRA)
- 401k with 6% Match
- 11 Paid Federal Holidays
- 120 hours of Paid Time Off (PTO)
- Company Outings and Trips
- Tuition Reimbursement, Skillset Training, and New/Renewed Certification assistance
- HomeFundIt Company Down Payment Match \- Employer match towards the down payment of buying a new home
DeNOVO Solutions is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, marital status, veteran status, sexual orientation, genetic information or any other protected characteristic under applicable law.
Ready to Apply?
Join DeNOVO Solutions and help shape the data science capability supporting emerging mission\-focused opportunities.
Salary Context
This $150K-$190K range is above the median for Data Scientist roles in our dataset (median: $157K across 236 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 3,823 AI roles we're tracking, Data Scientist positions make up 8% of the market. At DeNovo 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 $198,000 based on 808 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($170K) sits 14% below the category median. Disclosed range: $150K to $190K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
DeNovo Solutions AI Hiring
DeNovo Solutions has 1 open AI role right now. They're hiring across Data Scientist. Based in Aurora, CO, US. Compensation range: $190K - $190K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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