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About This Role
Overview:
Thank you for considering IT Concepts dba Kentro, where innovation drives opportunity and collaboration leads to success. Our dynamic community of experts is fully committed to advancing our customers' missions, fostering professional growth, and making a positive impact on our communities. By joining our supportive community, you will find that Kentro is dedicated to your personal and professional development. Together, we can drive meaningful change, spark innovation, and achieve extraordinary milestones.
Kentro is seeking a Data Scientist with an active TS/SCI security clearance to support mission\-driven analytics and data initiatives for U.S. government customers. In this role, you will analyze large and complex datasets to uncover insights, develop predictive models, and build data\-driven solutions that support operational, intelligence, and strategic decision\-making. Location: Onsite in Charlottesville, VA
Responsibilities:
- Analyze large, structured and unstructured datasets to identify patterns, trends, and actionable insights.
- Conducts data mining, exploratory analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal narrative products.
- Develop and implement machine learning models, predictive analytics, and statistical models to support mission objectives.
- Build data pipelines and data processing workflows to support scalable analytics solutions.
- Create data visualizations, dashboards, and reports to communicate findings clearly to stakeholders.
- Collaborate with data engineers, software developers, and mission analysts to integrate data science solutions into operational systems.
- Perform data cleaning, feature engineering, and exploratory data analysis (EDA).
- Apply advanced statistical methods and machine learning techniques to solve complex analytical problems.
- Support data\-driven decision\-making across government mission areas.
- Document methodologies, models, and analytical results.
- Contribute to Agile development cycles and technical design discussions.
Qualifications:
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related quantitative field.
- 3\+ years of professional experience in data science, analytics, or machine learning supporting software development, analytics or mission\-focused systems.
- Strong proficiency in Python or R for data analysis and modeling.
- Experience with data manipulation and analysis libraries (Pandas, NumPy, SciPy, or similar).
- Experience building data models and analytic capabilities that integrate into production software systems.
- Experience with machine learning frameworks such as Scikit\-learn, TensorFlow, or PyTorch.
- Strong understanding of statistics, probability, and predictive modeling and experience applying these to real\-world datasets.
- Experience with data visualization tools such as Tableau, Power BI, Matplotlib, or Plotly.
- Familiarity with SQL and relational databases.
- Experience supporting DoD, the Intelligence community, or other federal agency.
- Ability to communicate complex analytical concepts clearly to technical and non\-technical audiences.
- Certified in machine learning, data analytics, or cloud platforms.
- IAT Level II or III certified
Preferred Qualifications:
- Experience supporting Department of Defense (DoD), Intelligence Community (IC), or Federal Civilian agencies.
- Experience working with large\-scale data platforms (Spark, Hadoop, Databricks).
- Familiarity with cloud environments such as AWS, Azure, or Google Cloud.
- Experience building AI/ML solutions for operational or mission systems.
- Knowledge of natural language processing (NLP), computer vision, or graph analytics.
- Experience with data engineering concepts and ETL pipelines.
- Familiarity with DevSecOps and MLOps practices.
- Experience with geospatial analytics or time\-series analysis.
- Understanding of data governance, security, and compliance frameworks (NIST, FedRAMP, etc.).
- Experience working in classified environments or SCIF settings.
Clearance Requirement:
- Active U.S. Security Clearance (TS/SCI)
Preferred Personal Attributes:
- Strong analytical and problem\-solving mindset.
- Curiosity and passion for discovering insights through data.
- Ability to work independently in mission\-focused environments.
- Strong communication and collaboration skills.
- Detail\-oriented with a focus on accuracy and reproducibility in analysis.
Benefits:
The Company
We believe in generating success collaboratively, enabling long\-term mission success, and building trust for the next challenge. With you as our partner, let’s solve challenges, think innovatively, and maximize impact. As a valued member of our team, you have the unique opportunity to work in a diverse range of technology and business career paths, all while supporting our nation and delivering innovative technology solutions. We are a close community of experts that pride ourselves on creating an environment defined by teamwork, dedication, and excellence.
We hold three ISO certifications (27001:2013, 20000\-1:2011, 9001:2015\), two CMMI ML 3 ratings (DEV and SVC) and CMMC Level 2 Certification. Industry Recognition
Growth \| Inc 5000’s Fastest Growing Private Companies, DC Metro List Fastest Growing; Washington Business Journal: Fastest Growing Companies, Top Performing Small Technology Companies in Greater D.C.
Culture \| Northern Virginia Technology Council Tech 100 Honoree; Virginia Best Place to Work; Washington Business Journal: Best Places to Work, Corporate Diversity Index Winner – Mid\-Size Companies, Companies Owned by People of Color; Department of Labor’s HireVets for our work helping veterans transition; SECAF Award of Excellence finalist; Victory Military Friendly Brand; Virginia Values Veterans (V3\); Cystic Fibrosis Foundation Corporate Breath Award Benefits
We offer competitive benefits package including paid time off, healthcare benefits, supplemental benefits, 401k including an employer match, discount perks, rewards, and more. We invest in our employees – Every employee is eligible for education reimbursement for certifications, degrees, or professional development. Reimbursement amounts may fluctuate due to IRS limitations. We want you to grow as an expert and a leader and offer flexibility for you to take a course, complete a certification, or other professional growth and networking. We are committed to supporting your curiosity and sustaining a culture that prioritizes commitment to continuous professional development.
We work hard; we play hard. Kentro is committed to incorporating fun into every day. We dedicate funds for activities – virtual and in\-person – e.g., we host happy hours, holiday events, fitness \& wellness events, and annual celebrations. In alignment with our commitment to our communities, we also host and attend charity galas/events. We believe in appreciating your commitment and building a positive workspace for you to be creative, innovative, and happy. Commitment Equal Opportunity Employment \& VEVRAA
Kentro is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state or local law.
Kentro is strongly committed to compliance with VEVRAA and other applicable federal, state, and local laws governing equal employment opportunity. We have developed comprehensive policies and procedures to ensure our hiring practices align with these requirements.
As part of our VEVRAA compliance efforts, Kentro has established an equal opportunity plan outlining our commitment to recruiting, hiring, and advancing protected veterans. This plan is regularly reviewed and updated to ensure its effectiveness.
We encourage protected veterans to self\-identify during the application process. This information is strictly confidential and will only be used for reporting and compliance purposes as required by law. Providing this information is voluntary and will not impact your employment eligibility.
Our commitment to equal employment opportunity extends beyond legal compliance. We are dedicated to fostering an inclusive workplace where all employees, including protected veterans, are treated with dignity, respect, and fairness. How to Apply
To apply to Kentro Positions\- Please click on the job link and then click the blue “Apply” button at the top right of Job Description. Please upload your resume and complete all the application steps. You must fully submit the application for Kentro to consider you for a position. If you need alternative application methods, please email careers@kentro.us and request assistance.
Accommodations
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. Reasonable Accommodations may be made to enable qualified individuals with disabilities to perform the essential functions. If you need to discuss reasonable accommodations, please email careers@kentro.us.
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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 26,159 AI roles we're tracking, Data Scientist positions make up 2% of the market. At Kentro, 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 $204,700 based on 441 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Kentro AI Hiring
Kentro has 3 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span US, Charlottesville, VA, US.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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