ITmPowered

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.. 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.). Experience in statistical languages (R, Python, SQL, etc.). 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.. Experience querying databases and using statistical computer languages: R, Python, SQL, etc.

data scientist

Data Scientist - Big Data - Cyber - ITmPowered Consulting The Sr. Data Scientist - Big Data - Cyber will apply Data Science to solve 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: <ul><li>Analyze large amounts of data and develop statistical models to find patterns and solve problems that will help drive strategic business decisions.</li><li>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.)</li><li>Gather requirements for data, models, reports, and visualizations, and present solutions for stakeholders using: R, Tableau, SQL, Jupyter, Periscope, D3, ggplot, etc.</li><li>Look at cybersecurity and machine learning opportunities identifying opportunities and goals (detect threats, predict attacks, prediction, prevention, detection, response, monitoring)</li><li>Design and implementation of machine learning solutions using regression, model, clustering (KNN, K-means, Bayesian, Mean-shift), statistical profiling, inference, classification, and predictive analysis.</li><li>Leverage AI and Machine Learning in both supervised (classification, regression) and unsupervised scenarios (clustering, association, dimension reduction).</li><li>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.</li><li>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</li></ul> Qualifications for success: <ul><li>Bachelor's Degree in Data Science, Computer Science, Information Systems, Mathematics, Statistics, Engineering or similar (Masters Preferred)</li><li>Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, regression, classifications, etc.) and their real-world advantages drawbacks.</li><li>Experience with data architecture, data sets, building statistical models, model validation, and deployment.</li><li>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.</li><li>Experience with distributed data tools: Map Reduce, Hadoop, Spark, Hive, Impala, Hadoop, Spark, Cloudera.</li><li>Experience visualizing presenting data for stakeholders using: R, Tableau, Jupyter, Periscope, D3, ggplot, etc.</li><li>Experience in statistical languages (R, Python, SQL, etc.) manipulate data, draw insights from large data sets.</li><li>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.</li><li>Experience querying databases and using statistical computer languages: R, Python, SQL, etc.</li><li>Experience working with high volume data lakes, and large databases.</li><li>Demonstrated experience applying data science methods to real-world data problems</li></ul> Preferred Expertise <ul><li>Understanding of cyber security, computer network security, security protocols, encryption, security scanning, threat and vulnerability management, Technology Risk Assessment, cybersecurity assessment, IT Controls</li></ul> LOGISTICS: <ul><li>Local Denver resources only. No relocation provided.</li><li>Will be remote primarily but must be able to come into DTC office periodically after COVID Abates.</li><li>COVID-19 - Must be fully vaccinated OR provide medical or religious exemption.</li><li>W2 only - No sub vendors. Sponsorship NOT available. MUST PROVIDE DIRECT CONTACT INFORMATION TO APPLY.</li><li>You will need to be a US Citizen, 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.</li></ul>

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