Analyst 2 - Clinical Data - eTeam Inc.
TITUSVILLE, NJ 08560
About the Job
Remote
1) Data Engineer: manage core data infrastructure, ensuring data is available and accessible across the organization.
2) Analytics Engineer: build well tested, up to date and documented datasets that the rest of the company can use to answer their own questions.
3) Data Analyst: partner with business stakeholders to answer questions with data, build dashboards and reporting, and carry out exploratory analysis.
4) Data Scientist (Client Engineer): use statistics and machine learning to extract value from data: solving optimization problems, building prediction models, running A/B experiments and more.
Key Responsibilities Across ALL Roles:
Main responsibilities will include, but are not limited to:
" Align with business partners on requirements, success criteria and strategies for communications, user testing and deployment.
" Create new mechanisms to monitor for quality signals using outputs from analytics, including descriptive analytics, signal detection, natural language processing, machine learning, and time-series analysis.
" Apply analytical/statistical methods to complex and disparate data sources.
" Demonstrate Data Theory core competencies and literacies is required.
" Required Data Theory training is a must for ALL roles
Experience and Skills:
Required:
" Data Ontology Design, Generalized Contextual Modeling and Processing Mapping Skills Required.
" Experience with developing applications for advanced AI (e.g. Generative AI), Client, NLP, or another data science specialization is required.
" Experience with one or more of data engineering, product management, UI/UX design, decision science and front-end application development is required.
" Experience with building data science and data engineering solutions to real-world problems and datasets required.
" Proficiency in a modern data science language (Python and/or R) required.
" "Does it work?" attitude to building data science solutions. Agile Experience required.
" High level of organization and ability to balance multiple tasks required.
" Strong oral and written communication skills required
" Experience with fast-paced agile software development / DevOps / MLOps is required.
" Proficiency in building and using business intelligence / data visualization tools such as Spotfire, Tableau, QLIK
" DP 203 Certification or AWS Data Engineering Certification Preferred
1) Data Engineer: manage core data infrastructure, ensuring data is available and accessible across the organization.
2) Analytics Engineer: build well tested, up to date and documented datasets that the rest of the company can use to answer their own questions.
3) Data Analyst: partner with business stakeholders to answer questions with data, build dashboards and reporting, and carry out exploratory analysis.
4) Data Scientist (Client Engineer): use statistics and machine learning to extract value from data: solving optimization problems, building prediction models, running A/B experiments and more.
Key Responsibilities Across ALL Roles:
Main responsibilities will include, but are not limited to:
" Align with business partners on requirements, success criteria and strategies for communications, user testing and deployment.
" Create new mechanisms to monitor for quality signals using outputs from analytics, including descriptive analytics, signal detection, natural language processing, machine learning, and time-series analysis.
" Apply analytical/statistical methods to complex and disparate data sources.
" Demonstrate Data Theory core competencies and literacies is required.
" Required Data Theory training is a must for ALL roles
Experience and Skills:
Required:
" Data Ontology Design, Generalized Contextual Modeling and Processing Mapping Skills Required.
" Experience with developing applications for advanced AI (e.g. Generative AI), Client, NLP, or another data science specialization is required.
" Experience with one or more of data engineering, product management, UI/UX design, decision science and front-end application development is required.
" Experience with building data science and data engineering solutions to real-world problems and datasets required.
" Proficiency in a modern data science language (Python and/or R) required.
" "Does it work?" attitude to building data science solutions. Agile Experience required.
" High level of organization and ability to balance multiple tasks required.
" Strong oral and written communication skills required
" Experience with fast-paced agile software development / DevOps / MLOps is required.
" Proficiency in building and using business intelligence / data visualization tools such as Spotfire, Tableau, QLIK
" DP 203 Certification or AWS Data Engineering Certification Preferred
Source : eTeam Inc.