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About This Role
The Mission, Concepts and Capabilities (MCC) division of Applied Research Associates, Inc. (ARA) is seeking a Computational Data Scientist to join a multi-disciplinary team of engineers and scientists developing agentic AI models and visualization tools focused on data analytics for the Department of Defense. The ideal candidate has a passion for data science, data visualization, machine learning and artificial intelligence, analytics, and enjoys writing computer code. Representative tasks may include using Jupyter and Marimo Notebooks to create interactive training materials for weapons effects applications, building interactive visualizations and dashboards for sensor analytics, creating modern, adult learning tools for presentation and deployment within Jupyter Books, developing agentic AI tools with large language reasoning models for automating complex scientific analysis and advanced search and discovery tasks. This position will place you in a team of engineers and scientists developing a suite of software tools used by the defense community, to include interactive training materials, weapons effects modeling and simulation applications, and artificial intelligence solutions to aid research and development projects.
Hybrid work is permissible depending on the evolving project requirements.
What You’ll Do:
- Collect, curate, impute, and normalize structured and unstructured data
- Develop interactive visualizations and dashboards within Marimo and Jupyter notebooks to facilitate knowledge discovery and analysis using libraries such as Plotly, Bokeh, and HoloViz
- Develop machine learning algorithms and models using libraries such as SciKit-Learn, TensorFlow, and PyTorch
- Develop adult learning tools and applications within Jupyter Book
- Develop computer vision approaches to analyze images and video
- Conduct data analysis of outputs from engineering and first principles physics codes
- Deploy machine learning and analytics tools for operational use
- Support testing, evaluation, and demonstrations of software and analytics tools in unclassified and classified environments
- Take on new challenges and learn new skills to enhance algorithm and software performance in previously unanticipated ways
Required Qualifications:
- Bachelor’s degree in data science, computational science, computer science, mathematics, artificial intelligence, engineering, or related field with 2-4 years of experience OR Master’s degree in the same fields with 0-2 years of experience
- Strong Python programming skills
- Experience with Jupyter suite (e.g., Jupyter Lab, Jupyter Notebooks, Jupyter Book)
- Hands-on experience completing projects (academic or otherwise) in data science, data visualization, machine learning, and/or data analytics
- Eagerness to learn new tools and techniques
- US citizen with the ability to obtain and maintain a Department of Defense secret security clearance
Desired Qualifications:
- Previous internship or support to the Department of Defense
- Active security clearance
- Experience developing applications for ATAK or Android with Kotlin
- Advanced degree (MS or PhD) in data science, computational science, artificial intelligence, computer science, mathematics, engineering, or related field
- Experience with a variety of industry standard tools for data visualization and machine learning such as OpenCV, SciKit, R, TensorFlow, etc.
- Familiarity with interactive visualizations using tools such as MatplotLib, Plotly, HoloViz, Julia, D3, and Bokeh
- Programming experience in other memory safe by default languages such as Rust and Java
Compensation & Benefits: Pay Ranges: From $75,000.00 - $100,000.00 per year based on years of experience, degree and any special skills and knowledge that you may bring to the position. We mostly reserve the upper half of our compensation bands for internal growth. During all call with one of our recruiters or hiring managers, they can further clarify the salary range and total compensation. ARA offers competitive benefits that address our employees’ needs now and in the future. Learn more about each of our benefits at https://www.ara.com/benefits/
COMPANY INFORMATION:
Applied Research Associates, Inc. is an employee-owned international research and engineering company recognized for providing technically superior solutions to complex and challenging problems in the physical sciences. The company, founded in Albuquerque, NM, in 1979, currently employs over 2,000 professionals and continues to grow. ARA offices throughout the United States and Canada provide a broad range of technical expertise in defense technologies, civil technologies, computer software and simulation, systems analysis, environmental technologies, and testing and measurement. The corporation also provides sophisticated technical products for environmental site characterization, pavement analysis, and robotics.
At ARA, employees are our greatest assets. The corporation realizes that employee ownership fosters greater creativity and initiative along with higher performance and customer satisfaction levels. ARA gives employees the tools, training, and opportunities to take more active roles as owners. The culture is challenging and innovation and experimentation are the norm. Employees are eligible for contributions which not only add to the company’s success, but also their own through the Employee Stock Ownership Plan (ESOP). The motto, “Engineering and Science for Fun and Profit” sums up the ARA experience. For additional information and an opportunity to join this unique workplace, please apply at careers.ara.com.
Please apply at www.careers.ara.com for the Computational Data Scientist position.
Experience
Required
- Less than 4 year(s): Experience in programming and data skilsl
Education
Required
- Bachelors or better in Data Science or related field
Preferred
- Masters or better in Data Science or related field
Behaviors
Required
- Team Player: Works well as a member of a group
- Innovative: Consistently introduces new ideas and demonstrates original thinking
- Enthusiastic: Shows intense and eager enjoyment and interest
- Detail Oriented: Capable of carrying out a given task with all details necessary to get the task done well
- Dedicated: Devoted to a task or purpose with loyalty or integrity
Motivations
Required
- Self-Starter: Inspired to perform without outside help
- Growth Opportunities: Inspired to perform well by the chance to take on more responsibility
- Ability to Make an Impact: Inspired to perform well by the ability to contribute to the success of a project or the organization
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.
Salary Context
This $75K-$100K range is in the lower quartile for Data Scientist roles in our dataset (median: $161K across 138 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 9,079 AI roles we're tracking, Data Scientist positions make up 4% of the market. At Applied Research Associates, Inc, 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 1,503 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($87K) sits 54% below the category median. Disclosed range: $75K to $100K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Applied Research Associates, Inc AI Hiring
Applied Research Associates, Inc has 1 open AI role right now. They're hiring across Data Scientist. Based in Alexandria, VA, US. Compensation range: $100K - $100K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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