Interested in this Data Scientist role at Trideum Corporation?
Apply Now →Skills & Technologies
About This Role
Senior Data Scientist / Analytics Lead
Full\-time
Huntsville, AL
About Us
Trideum Corporation is a 100% employee\-owned company, committed to embracing the world’s toughest challenges with a servant’s heart. Through dedicated hard work and commitment, we provide distinctive quality and unparalleled customer service in all aspects of our business. We also know that our employees are the key to our success, and it is our mission to take care of them so they can take care of our customers and communities where we live, work, and play.
Position Summary
As the Data Scientist and Analytics Lead, you will serve as the principal architect for data traceability and advanced analytics in support of the Army Materiel Command (AMC) Chief Technology Officer (CTO). In this critical advisory role, you will design the robust analytical models required to transform raw operational data into actionable leadership insights. Your work will empower enterprise senior leaders with the analytical depth and strategic frameworks necessary to make informed, defensible decisions regarding technology investments, pilot programs, and digital modernization initiatives.
You will lead the development of a comprehensive suite of enterprise\-level assessments, establishing a continuous, disciplined evaluation framework that serves as a single source of truth for the organization. By integrating advanced analytics, artificial intelligence pipelines, and operational dashboards into enterprise systems, you will create a highly traceable record of evidence that directly aligns technology initiatives with strategic mission priorities. This position is ideal for an expert who thrives on translating complex technical ecosystems into clear, executive\-ready decision support products.
What You’ll Do
Responsibilities include, but are not limited to:
- Design and implement advanced analytical models that transform raw operational and technical data into actionable leadership insights.
- Establish and maintain data traceability methodologies to ensure a disciplined linkage from source data and assumptions through to final leadership recommendations and decisions.
- Develop and integrate artificial intelligence (AI) pipelines and operational dashboards within enterprise platforms, such as Army Vantage, to provide real\-time decision support and consumption tracking.
- Define rigorous success criteria, precise data requirements, and Key Performance Indicators (KPIs) for emerging technology pilot programs before they are initiated.
- Conduct comprehensive, repeatable assessments measuring technical maturity, operational efficiency, feasibility, cyber risk, and program alignment across the technology portfolio.
- Produce high\-level executive decision support products, including formal options papers, executive memoranda, briefing decks, and recurring portfolio dashboards.
- Provide the analytical rigor required to evaluate technology sandbox initiatives and establish standardized metrics for post\-evaluation After\-Action Reviews (AARs).
Requirements and Qualifications
- Bachelor’s Degree from an accredited school in a technical discipline (e.g., data science, engineering, mathematics, science, computer science, etc.).
- Extensive proven experience functioning as a principal data architect or analyst, specifically designing models that translate complex data into executive\-level insights.
- 10\+ years of relevant professional experience.
- Expertise in languages like Python, R, and SQL; data visualization software like Tableau, Power BI, or Qlik; and data management platforms like ADVANA, Palantir Foundry, Databricks, Snowflake, and Azure Synapse Analytics.
- Strong background in establishing data traceability methodologies and evidence\-based decision support frameworks for large\-scale enterprise environments.
- Experience defining operational metrics, Key Performance Indicators, and strict success criteria for technology pilots, software applications, or capability assessments.
- Exceptional ability to produce executive\-ready communication products, briefing materials, and strategic documentation for senior leadership.
- Demonstrated ability to build, deploy, and manage artificial intelligence pipelines and comprehensive operational dashboards.
- U.S. citizenship and an active Secret security clearance with the ability to obtain/maintain a Top Secret/Sensitive Compartmented Information (TS/SCI) clearance.
Desired Qualifications
- Master’s Degree from an accredited school in a technical discipline (e.g., data science, engineering, mathematics, science, computer science, etc.).
- Familiarity with the Army Materiel Command mission, including broader Department of War Supply Chain and Organic Industrial Base (OIB) operations.
- Deep understanding of assessment frameworks utilized to measure technical debt, application lifecycle health, and overall enterprise architecture fit.
- Prior experience providing direct advisory support to a Chief Technology Officer, Chief Information Officer, or similar enterprise\-level executive function.
- Direct experience developing models or dashboards within Army Vantage or similar Department of War enterprise data platforms.
- Knowledge of technology sandbox environments, safe testing protocols, and "test\-before\-network" evaluation frameworks.
We Take Care of Our People
Whether you’re looking to launch a new career or grow an existing one, Trideum is the type of company where you can balance great work with great life because we believe that taking care of our people is the right thing to do. Trideum offers:
- Competitive pay based on the work you do here and not your previous salary.
- Traditional benefits such as medical, dental, vision, life, disability, and 401k matching.
- Employee Stock Ownership Plan (ESOP).
- Paid leave and the ability to cash out leave.
- Free access to certified financial planners, wellness and support services, and discount programs.
- Education assistance and professional development opportunities.
- And much more.
Ready to Apply?
Start Your Application now!
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, sexual orientation, gender identity, or any other characteristic protected by law. People with disabilities who need a reasonable accommodation to apply or compete for employment with Trideum may request such accommodation(s) by contacting Human Resources at 256\.704\.6123 or [email protected].
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 Trideum Corporation, 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. Senior-level AI roles across all categories have a median of $230,000.
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.
Trideum Corporation AI Hiring
Trideum Corporation has 2 open AI roles right now. They're hiring across Data Scientist. Positions span Killeen, TX, US, Huntsville, AL, US.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.