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About This Role
In a world of possibilities, pursue one with endless opportunities. Imagine Next!
At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what’s possible. Job Description:
Parsons is looking for a talented Senior Data Scientist to join our growing team!
In this role you will support key activities in defense of emerging threats in the cybersecurity domain. You will work directly with our software engineering and threat analyst teams to model complex data in an environment comprised of many databases and varying technology stacks. You will support key activities in defense of emerging threats in the cybersecurity domain and work as part of a team that develops and tailors capabilities with the common goal to prevent and eradicate threats to critical U.S. systems.
What You'll Be Doing:
- Develop statistical, and graph\-based algorithms to analyze and make sense of data sets.
- Clean and structure disparate data received from a globally dispersed customer base.
- Provide insight into dataset structures and produce data visualizations that are consumable by both technical an non\-technical audiences.
- Translate mission customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes.
- Develop and implement statistical, and machine learning techniques to create descriptive and predictive analytics.
- Evaluate and validate the performance of analytics using standard techniques and metrics and oversee development of individual analytic development efforts guiding them toward solutions that can scale to large datasets.
- Work in close partnership with subject matter experts, software engineers, and cloud developers to guide the formulation of analytics to production.
What Required Skills You'll Bring:
- Active TS/SCI security clearance with Polygraph
- At least 10 years of experience and a Bachelor of Science Degree in Master’s Degree or Doctoral Degree may be substituted for some experience.
- 7\+ years’ experience in two or more of the following: designing/implementing machine learning, data mining, advanced analytical algorithms, advanced statistical analysis, artificial intelligence, or software engineering with data analysis software (R, Python, SAS, MATLAB).
- Experience with Windows server management and Power BI Report Service.
- Proficiency with Python/Jupyter Notebooks, SQL and relational databases, ElasticSearch/Kibana/OpenSearch. Experience with Java is also a plus.
- Background working with analyst teams including conducting data analysis and creating data visualizations. Experience with graph analytics, data pipelines, and IP\-based network data is a plus, but not required.
- Experience working within a cybersecurity mission environment using tools and capabilities to generate threat intelligence. This includes working with cybersecurity analyst teams to perform data analysis and a deep understanding of adversary tradecraft.
Preferred Experience:
- Bachelor of Science Degree in a quantitative discipline such as statistics, mathematics, or a Computer Science degree.
Security Clearance Requirement:
An active Top Secret SCI w/Polygraph security clearance is required for this position.
This position is part of our Federal Solutions team.
The Federal Solutions segment delivers resources to our US government customers that ensure the success of missions around the globe. Our intelligent employees drive the state of the art as they provide services and solutions in the areas of defense, security, intelligence, infrastructure, and environmental. We promote a culture of excellence and close\-knit teams that take pride in delivering, protecting, and sustaining our nation's most critical assets, from Earth to cyberspace. Throughout the company, our people are anticipating what’s next to deliver the solutions our customers need now.
Salary Range: $125,100\.00 \- $225,200\.00
We value our employees and want our employees to take care of their overall wellbeing, which is why we offer best\-in\-class benefits such as medical, dental, vision, paid time off, 401(k), life insurance, flexible work schedules, and holidays to fit your busy lifestyle!
Parsons is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, veteran status or any other protected status.
We truly invest and care about our employee’s wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest—APPLY TODAY!
Parsons is aware of fraudulent recruitment practices. To learn more about recruitment fraud and how to report it, please refer to https://www.parsons.com/fraudulent\-recruitment/.
COMPETITIVE BENEFIT OFFERINGS
Financial Wellness
We care about your financial wellbeing. Parsons offers competitive pay and retirement plans to help you build wealth for the future while giving you the flexibility to diversify your investments.
Work Life Harmony
Balance in life is important and time away from the office is imperative to allow you to refresh and focus your attention on the things that matter to you. Parsons supports your time away by providing paid time off and paid flexible holidays.
Career Development
We are committed to fostering the personal and professional growth of our employees. Develop and advance yourself though our comprehensive training, educational and mentorship programs.
Veteran Support
We provide Industry leading benefits to support veterans and active\-duty members to provide security for you and your family by offering robust leave and benefits; including paid active\-duty military leave and paid time off when transitioning back to civilian life.
Mind \& Body
At Parsons we inspire healthier habits, heathier minds, and a healthier you through our wellness program. Participate in our weekly Meditation Mondays and Wellness Wednesdays. Wellness, at Parsons, is more than just your annual checkup.
Health
Health is not a one size fits all. At Parsons, we offer a robust Employee Assistance Program as well as comprehensive medical, dental and vision plans through large, national carriers with the choice of regional PPO, HDHP, or HMO networks.
Salary Context
This $125K-$225K range is above the median for Data Scientist roles in our dataset (median: $160K across 245 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 4,133 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Parsons, 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 868 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,778. This role's midpoint ($175K) sits 12% below the category median. Disclosed range: $125K to $225K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Parsons AI Hiring
Parsons has 8 open AI roles right now. They're hiring across AI Software Engineer, Data Scientist, Research Scientist, AI/ML Engineer. Positions span Annapolis Junction, MD, US, Aberdeen, MD, US, Remote, US. Compensation range: $111K - $332K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, 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 Safety roles lead at $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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