Title: Data Scientist
Location - In Office. Candidate should go into the Oracle Office daily. Ideally in one of these offices because we have teams in these offices:
i. Santa Clara, CA
ii. Redwood City, CA
iii. Austin, TX
iv. Reston, Virginia
v. Seattle, WA
Duration: 12 months
Pay Rate: $55/hr
Description:
Job Description: Access, cleanse, compile and transform disparate data sets to conduct exploratory and pre-defined analyses using scientifically valid techniques and generate meaningful insights
Assist with feasibility studies to identify data availability, quality and modeling requirements and dependencies
Support modern data storage, movement, and transformation architectures and techniques to extract and engineer features from any scale structured or unstructured data in health, IT system, business process, or external data
Contribute to discovery or engineering of explanatory features in high-dimensionality collections of data that relate to clinically, financially, and/or operationally important use-cases using scientifically valid techniques
Support iterative selection and application of modern statistical and machine learning techniques and evaluation methods to engineered features to derive a best candidate model
Interact with business teams and leaders to identify relevant questions and issues for data analysis and experimentation that support business needs or problems.
Propose new uses for existing data sets or sources, algorithms and predictive models
How many interviews will be required? 4 interviews
a. Tech Screen
b. Hiring Manager
c. Coding
d. System Design
. Three qualifications you are looking for:
a. Languages: Python, Java, SQL
b. Building Dashboards such as Grafana, OpenSearch, Oracle Analytics Cloud
c. Cloud Development such as (AWS, Microsoft Azure, Google Cloud, OCI Cloud) and building ETL Pipelines
d. Good to have: AI experience
. Is Source Code needed?
a. Yes
. Any other helpful information?
a. Engineer will be part of a 5 member team building Dashboards to provide insights. This will include building out the ETL pipeline and the front end dashboard. Later we want to transform the team to also build AI tools to help predict causes and triage outages in the
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