Overview
On Site
Depends on experience
Contract - W2
Skills
Medical devices
Data Science
Network security
Big data
Risk management
Security operations
Data management
Statistical models
Patch Management
Risk assessment
Data security
Machine Learning (ML)
k-means clustering
Mean-shift
Software security
Identity management
Intrusion detection
Forensics
Endpoint protection
Computer science
Information systems
Linear regression
Unsupervised learning
Deep learning
Extract
transform
load
Time series
Programming languages
Shell scripting
Cyber security
Computer networking
Vulnerability management
IT risk
Federal government
Data
Artificial intelligence
Transformation
Management
IMPACT
Splunk
Configuration management database
Inventory
CyberArk
Network
Governance
Design
Regression analysis
Clustering
k-nearest neighbors
Wireless communication
Cloud computing
Malware analysis
Firewall
WAF
Analytics
IP
Mathematics
Statistics
Algorithms
Software deployment
Visualization
R
Tableau
Jupyter
Python
NumPy
PySpark
Scala
Java
SQL
Apache Spark
Apache Hadoop
Database
Encryption
Logistics
DTC
Security clearance
PASS
Job Details
Data Scientist (AI/ML) - Medical Device Cybersecurity - ITmPowered Consulting
The Sr. Data Scientist will apply Data Science to enterprise Medical Device Cybersecurity, Network security, Attacks & Events. Leverage big data in support of an enterprise scale Medical Device Cybersecurity program spanning Risk Management, Cyber Digital Transformation, Threat Management, Network Security, End Point Security, IT Controls, Security Operations and Identity and Data Management. Will have direct impact providing strategic insight into Medical Device cybersecurity protection and improving networking security.
How you'll make an impact:
Qualifications for success:
Preferred Expertise
Logistics:
The Sr. Data Scientist will apply Data Science to enterprise Medical Device Cybersecurity, Network security, Attacks & Events. Leverage big data in support of an enterprise scale Medical Device Cybersecurity program spanning Risk Management, Cyber Digital Transformation, Threat Management, Network Security, End Point Security, IT Controls, Security Operations and Identity and Data Management. Will have direct impact providing strategic insight into Medical Device cybersecurity protection and improving networking security.
How you'll make an impact:
- Analyze large amounts of data and develop statistical models to find patterns and solve problems that will help drive strategic business decisions.
- Analyze data from numerous sources (Splunk, Qualis, CMDB/Asset Inventory, CyberArk, Armis, ForeScout, Automated Patch Management systems, Threat and Vulnerability, Network Traffic, Governance and Standards data, Risk Assessment data, Security baselines, etc.)
- Look at cybersecurity and machine learning opportunities identifying opportunities and goals (detect threats, predict attacks, prediction, prevention, detection, response, monitoring)
- Design and implementation of machine learning solutions using regression, model, clustering (KNN, K-means, Bayesian, Mean-shift), statistical profiling, inference, classification, and predictive analysis.
- Leverage AI and Machine Learning in both supervised (classification, regression) and unsupervised scenarios (clustering, association, dimension reduction).
- Looking at data across Network Security, network traffic analysis, Network security scanning (Wired, Wireless, cloud), Endpoint (anti-malware), Application Security (micro firewalls, WAF, Data firewalls), User Behavior Analytics, Device behavior analytics, access management. Security of data in transit, at rest, historically.
- Network Protection, Network Traffic Analytics, IP Traffic, Ports, intrusion detection. Identify different classes of network attacks - scanning and spoofing. Network anomaly detection, Encrypted traffic classification, Clustering for forensic analysis. Medical Device endpoint protection
Qualifications for success:
- Bachelor's Degree in Data Science, Computer Science, Information Systems, Mathematics, Statistics, Engineering or similar (Masters Preferred)
- Experience with a range of machine learning techniques: linear regression, classifications, random forest, clustering, supervised and unsupervised learning, graph algorithms, etc.
- Experience in Machine, and Deep Learning frameworks, model validation and deployment tools, data pipeline technologies, and visualization and data storytelling tools (R, Tableau, Jupyter, etc.).
- Advanced knowledge of statistical concepts such as regressions, time series, mixed model, Bayesian methods, clustering, classification, and graph models to analyze data and provide insights.
- Expertise in common data science toolkits and programming languages, including R, Python (including SciPy, NumPy, and/or PySpark) and/or Scala, Java, SQL, and shell scripting.
- Hands-on experience with Spark and Hadoop.
- Experience working with high volume data lakes, and large databases.
- Demonstrated experience applying data science methods to real-world data problems
Preferred Expertise
- Understanding of cyber security, computer network security, security protocols, encryption, security scanning, threat and vulnerability management, Technology Risk Assessment, cybersecurity assessment, IT Controls
Logistics:
- Local Denver resources only. No relocation provided.
- Will be remote primarily but must be able to come into DTC office periodically after COVID Abates.
- COVID-19 - Must be fully vaccinated OR provide medical or religious exemption.
- W2 only - No sub vendors. Sponsorship NOT available. Must have direct contact information on resume to apply.
- You will need to be a , and with the ability to obtain US Government TOP SECRET clearance, as well as successfully pass a 12 panel drug screen and 10 year background check, in order to meet eligibility requirements for access to classified information.