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About This Role
Job Title: Data Scientist
Clearance Required: US Citizen, Public Trust Clearance
Work Location: Hybrid, Camp Springs, MD
Alpha Omega is looking for a Data Scientist to join our team in support of a large security operations program with a federal client. Our threat hunting team seeks to uncover the presence of attacker tactics, techniques, and procedures (TTP) to support the customers’ mission of ensuring confidentiality, integrity, and availability of the infrastructure for the agency to achieve its mission. The Threat Hunt Analyst will apply the proper techniques and procedures for the identification, collection, examination, and analysis of data while preserving the integrity of the information and maintaining a strict chain of custody.
Responsibilities:
- Apply the proper techniques and procedures for the identification, collection, examination, and analysis of data while preserving the integrity of the information and maintaining a strict chain of custody
- Advanced traffic analysis (at the packet level) and reconstruction of network traffic to discover anomalies, trends, and patterns affecting the customers networks
- Work with engineers to ensure large data sets and tools are being used effectively to support machine learning and data science analysis techniques.
- Develop algorithms and models based on analyst use cases for security log data.
- Support Hunt Team operations by leveraging innovative approaches to incident discovery.
- Assist in other areas of SOC operations as needed such as data trending, statistical analysis, incident investigation/mitigation, etc.
Required Skills/Experience:
- Data and predictive analytics experience especially using log/incident data.
- Experience ingesting and analyzing data from AWS, MS ATP, Tanium and other security tools into Splunk or AWS/Hadoop.
- Developing and applying ML models on large sets of streaming and static data to uncover insights
- Understanding of Security domain and experience applying data analytics in security domain
Preferred Skills/Experience:
- Performing NETFLOW or PCAP analysis using Wireshark, Cisco Stealthwatch, AWS VPC Flow logs, is a big plus
- Configuring Splunk modules or AWS ML services or other data analytics tools to assist in security anomaly and hunt detection
- Network, live system, sandbox static and RAM/memory forensic malware analysis
Required Certifications:
- At least one of the following: Security\+, CYSA\+, GCIH, ISC2 CISSP, GSE, GREM, GAWN, GCIA, GPPA, GSEC, GCED, GSLC, GSNA, GCFA, or other comparable certification
Required Education:
- Minimum Bachelors in Computer science or Data Analytics
Salary and Benefit Information:
The likely salary range for this position is $117,000 – $137,000\. This is not, however, a guarantee of compensation or salary. There are multiple factors that are considered in determining final pay for a position, including, but not limited to, relevant work experience, skills, certifications and competencies that align to the specified role, education and certifications as well as contract provisions regarding labor categories that are specific to the position and could fall outside of this range.
Application Deadline: September 30, 2026
Joining the Alpha Omega team entitles you to participate in all retirement benefits, plans of deferred compensation, health and insurance benefits, and other such benefits as set forth in the company’s policy and benefits manuals. See below, to name a few:
- PTO including paid parental, military, and bereavement leave
- Eleven (11\) paid Federal holidays, five of which are floating holidays (as designated by the company’s holiday schedule each year)
- Health and Dental Insurance (including 100% employer paid premiums for employee coverage under the HDHP health plan)
- Life Insurance, STD/LTD term disability coverage, with employer paid premiums
- 401 (k) plan with a match that is 100% vested after you complete two years of service
- FSA/DFSA/HSA flexible benefit plans
- Annual Tuition \& Professional Development Reimbursement benefit
We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.
Our Company:
Alpha Omega is an award\-winning solutions provider dedicated to delivering mission\-enabling technology and strategic solutions for our customers. Since our founding in 2016, we have grown to over 700 employees nationwide consisting of former operators, technologists, and strategists who bring decades of government and industry experience. They are united by one purpose: ensuring our nation’s continued global leadership.
We have a unified operating model providing technical capabilities and solutions for customers across two main business units:
- National Security – supporting agencies such as the Department of Homeland Security (DHS), Navy, Air Force, Army, and the Department of State (DOS).
- National Resilience – supporting agencies such as Federal Deposit Insurance Corporation (FDIC), Treasury, Health \& Human Services (HHS), National Institutes of Health (NIH), National Oceanic and Atmospheric Administration (NOAA) and the United States Department of Agriculture (USDA)
Through strategic partnerships, intellectual property, and relentless drive for innovation, Alpha Omega is shaping the future of government technology. We are proud to be a Virginia Best Places to Work 8 times, an Inc. 5000 honoree 7 times, and a Washington Post Top Workplaces 4 times. Join us in driving transformation that secures the nation's future.
Culture and Values:
Guided by our core values—Harmony, Engagement, Accountability, Resourcefulness, and Tenacity (HEART)— we foster a culture of innovation, collaboration, and continuous learning and are committed to delivering high\-impact solutions. We recognize and reward hard work.
Alpha Omega's culture is driven by our values and mission. We invest in top talent through mentorship, growth, and meaningful work. We value individuality, reward integrity, and foster a diverse, high\-performing team united by purpose\-at work, in service, and in the community.
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 (https://www.eeoc.gov/poster) notice from the Department of Labor.
Salary Context
This $117K-$137K range is in the lower quartile for Data Scientist roles in our dataset (median: $155K across 226 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 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Alpha Omega Integration, 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 $192,890 based on 463 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($127K) sits 34% below the category median. Disclosed range: $117K to $137K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Alpha Omega Integration AI Hiring
Alpha Omega Integration has 1 open AI role right now. They're hiring across Data Scientist. Based in Camp Springs, MD, US. Compensation range: $137K - $137K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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