Overview
On Site
$Based on experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 9 month(s)
Skills
IT consulting
Real-time
Computational Science
Big data
Machine Learning (ML)
Logistic regression
Data acquisition
Data Analysis
Data Visualization
Data quality
Version control
Incident management
Security audit
Data
Agile
SAP BASIS
Profit and loss
Python
SQL
Apache Hive
Apache Hadoop
Apache Spark
Algorithms
Support vector machine
k-nearest neighbors
XGBoost
Statistics
Training
Testing
Probability
GitHub
Continuous integration
Continuous delivery
Metrics
IMPACT
Network
Job Details
Stellar Consulting Solutions is a boutique business & technology consulting company headquartered in Atlanta, GA. We deliver high quality, agile, and experienced workforce for niche technology projects of any scale. We help forward thinking clients to solve specific problems by understanding their needs and align talent that can move fluidly
to match skill supply and demand on a real-time basis.
to match skill supply and demand on a real-time basis.
Stellar Consulting has a unique combination of technical and digital skills to recruit, engage, and retain qualified talent. We have a stellar reputation for striving to achieve high ethical standards. Our use of Innovative techniques and industry best practices has made us one of the fastest growing boutique firms delivering to enterprise business.
TITLE:Data Scientist V
LOCATION:San Jose CA
Job Description:
Required Skill Sets:
Experience with scientific computing language and big data knowledge, including Python, SQL, Hive, Hadoop, Spark etc.
Experience with common machine learning algorithms (SVM, KNN, logistic regression, random forest, XGBoost, Neural Networks, etc.)
Develop and maintain ML/Stats models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.
Developed skills in the application of scientific methods to practical problems through exploratory data analysis, hypothesis testing and data visualization to reach robust conclusions.
Understanding of statistical probability distributions, bias, error and power as well as sampling and resampling methods.
Expertise in the manipulation, integration, processing and interrogation of large datasets. Maintain data quality and support data access.
Experience with source control tools such as GitHub and related CI/CD processes
Ability to tackle ambiguous and undefined problems and thrive with minimal oversight and process.
Ability to communicate and discuss complex topics with technical and non-technical audiences
Better to have or willing to learn:
Leverage data to inform strategic directions of safety signal development, aid in incident response, automate detection and enforcement, and provide intelligence on ecosystems.
Operationalize and evolve Threat Detections metrics that measure the impact of our targeted enforcement.
Feel comfortable with analyzing and telling stories of security, audit and network data, and understand the context of monitor systems and threat detection.
Disseminate intelligence gathered to other safety stakeholders and executive decision makers.
Experience with common machine learning algorithms (SVM, KNN, logistic regression, random forest, XGBoost, Neural Networks, etc.)
Develop and maintain ML/Stats models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.
Developed skills in the application of scientific methods to practical problems through exploratory data analysis, hypothesis testing and data visualization to reach robust conclusions.
Understanding of statistical probability distributions, bias, error and power as well as sampling and resampling methods.
Expertise in the manipulation, integration, processing and interrogation of large datasets. Maintain data quality and support data access.
Experience with source control tools such as GitHub and related CI/CD processes
Ability to tackle ambiguous and undefined problems and thrive with minimal oversight and process.
Ability to communicate and discuss complex topics with technical and non-technical audiences
Better to have or willing to learn:
Leverage data to inform strategic directions of safety signal development, aid in incident response, automate detection and enforcement, and provide intelligence on ecosystems.
Operationalize and evolve Threat Detections metrics that measure the impact of our targeted enforcement.
Feel comfortable with analyzing and telling stories of security, audit and network data, and understand the context of monitor systems and threat detection.
Disseminate intelligence gathered to other safety stakeholders and executive decision makers.