Your Models Get Deployed. Actually.
In most data science shops, your brilliant ML algorithm becomes a proof-of-concept that dies in a Jupyter notebook.
With our client? 90% deployment rate. Your models go into production. Your insights drive decisions. Your work matters.
After decades serving the Intelligence Community, they've cracked the code on what separates data science theater from data science impact.
Why This Actually Matters
Well, you didn't come this far to build models that just collect dust, did you? You're probably ready for work where :
- Your feature engineering directly supports IC analysts
- Your algorithms get integrated into operational workflows
- Your visualizations inform senior-level decision makers
- Your experiments generate data that drives real-world action
This isn't data science kindergarten. This is the Intelligence Community's hardest problems - where your models mean the difference between security and risk, waste and efficiency, confusion and clarity.
What You'll Solve
Machine Learning & Algorithm Development
Develop ML, data mining, statistical, and graph-based algorithms for complex IC datasetsPrototype multiple approaches and select final models based on rigorous performance metricsBuild experiments to generate synthetic data when training sets are unavailableImplement production-ready algorithms within analyst workflowsData-Driven Intelligence
Partner with SMEs to translate manual analysis into automated analyticsGenerate reports and visualizations that summarize massive datasetsProvide data-driven insights to IC customers across the NSGDevelop feature vectors optimized for machine learning pipelinesTechnical Leadership (Level 3 / Principal)
Guide teams in analytic development processesEvaluate analytics using cross-validation, ROC curves, confusion matricesScale solutions to handle extremely large datasetsCollaborate with software engineers on production deploymentsAll roles support Defense and Intelligence customers. On-site at Fort Meade.
What You Need
Clearance : TS / SCI with Full Scope Polygraph (required)
Education & Experience :
Data Scientist Level 2 :
Bachelor's + Master's in quantitative discipline (Statistics, Mathematics, Operations Research, Engineering, Computer Science)5 years analyzing datasets and developing analytics5 years programming with R, Python, SAS, or MATLABOR 2 additional years of experience substitutes for Master'sOR PhD substitutes for 3 years of experienceData Scientist Level 3 :
Bachelor's + Master's (or higher) in quantitative discipline10 years analyzing datasets and developing analytics10 years programming with R, Python, SAS, or MATLABPhD substitutes for 4 years of experiencePrincipal Data Scientist :
Bachelor's + Master's (or higher) in quantitative discipline15 years analyzing datasets and developing analytics10 years programming with R, Python, SAS, or MATLABPhD substitutes for 4 years of experienceTechnical Skills That Matter Here
Core Competencies :
Python, R, SQL (you're fluent in all three)Machine learning algorithms & model tuningStatistical analysis & mathematical modelingFeature engineering & data preprocessingModel validation techniques (cross-validation, ROC, confusion matrices)Data visualization & storytellingGeospatial Intelligence Focus (Select Roles)
ESRI ArcGIS, geospatial software applicationsTimeseries modeling & forecastingLarge Language Models (LLM) developmentSagemaker, Databricks, HueCollections performance analysisMulti-source GEOINT strategiesLeadership Skills (Senior Roles)
Team leadership & analytic delegationRequirements gathering with customers & SMEsAlgorithm evaluation & recommendationProduction system transition guidancePerformance monitoring & quality controlWhy People Leave the Big Boys... For Us
💰 Compensation That Recognizes Expertise
Competitive salary packages exceeding $200K for experienced candidatesAnnual merit increases + performance bonusesESOP profit-sharing (actual ownership in what you build)401(k) with 3% match, immediate vestingUp to $10K referral bonuses🎯 Impact Over PowerPoint
90% deployment rate vs. 20% industry averageYour models go into operational systems, not proof-of-concept purgatory250+ projects delivered over decades of consistent growthDirect collaboration with IC customers and SMEs🧠 Continuous Learning Culture
Weekly company-wide Tech Talks (learn from peers)$5,250 / year tuition reimbursementLinkedIn Learning, Statistics.com accessDedicated professional development time every weekInnovation Lab for exploring emerging ML techniquesExposure to state-of-the-art algorithms and frameworks⚖️ Work-Life Balance (Not a Myth)
Reasonable hours—no burnout cultureExtremely flexible PTO (including your birthday)Sabbaticals every 5 years (2 weeks + $12K stipend at 10 years)$100 / month fitness reimbursementRemote options where mission allowsEmployee Assistance Program support🤝 Values-Driven Culture
You Might Be Our Next Data Scientist If...
✓ You question your model's assumptions until you find the truth
✓ You care as much about deployment as you do about accuracy scores
✓ You believe the best data scientists explain complex results simply
✓ You'd rather build one robust pipeline than ten fragile notebooks
✓ You get excited when subject matter experts challenge your approach
✓ You want to see your work actually used by Intelligence Community analysts
The Reality Check
This isn't remote. You'll be on-site at Fort Meade supporting critical IC missions.Full Scope Poly is mandatory. No exceptions, no sponsorships in progress.We hire for careers, not contracts. More than 30 years of stability proves it.Your work is classified. You won't be publishing papers or posting about it online.But if you're cleared, curious, and tired of building models that never escape your laptop? We should talk.