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Software Engineer - Device Integration

๐Ÿ’ฐ $100,000 - $130,000 ๐Ÿ“… 01/25/2024

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Senior AI & Data Technical Program Manager

๐Ÿ’ฐ $200 - $140,000 ๐Ÿ“… 07/03/2024

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Job Description

* _Job Purpose/Summary *_

This position combines project management with a data-focused individual
contributor analyst role. As a technical coordinator, youโ€™ll plan and oversee
multi-year initiatives across scientific, product, and engineering domains,
while also becoming technically involved to draw insights from data. Your role
involves collaborating with data engineers, scientists, and software engineers
to ensure system and data quality. Youโ€™ll also manage JIRA-based project
activities, facilitate clear communication, and drive successful product
delivery.

* _Duties and Responsibilities *_

Plan and coordinate multi-year technical initiatives across scientific,
product, and engineering domains
Support receiving collaborator datasets, including identifying technical and
security requirements, performing quality assessment of data.
Leverage business intelligence tooling to generate visualizations of datasets
for technical and non-technical consumers.
Perform limited data engineering tasks, including ingestion and cleaning of
data
Collaborate closely with data engineers, data scientists, software engineers
and other internal and external technical contributors via pull requests,
written documentation, and other communication channels to ensure system and
data quality.
Lead JIRA-based project management activities, ensuring efficient workflows,
clear communication, and successful product delivery

* _Qualifications *_

Minimum:
Graduate degree in computer science, information science, or related field, or
mix of education and work experience.
10+ years' experience providing project and product management to data-focused
organizations
4+ years' experience working with cloud data infrastructure
2+ yearsโ€™ hands-on experience working with data, performing analyses and
creating visualizations

Preferred:
Exposure to a product-driven machine learning organization with deployed
customer-facing capabilities.
Exposure to a big data environment, including tools for clustered computing
(e.g., Spark, Dask, streaming) and large-scale data storage.