What are the responsibilities and job description for the Principal Data Science Engineer position at Macpower Digital Assets Edge?
Benefits : Medical, Dental, Vision, Paid time off, Stock plan, Remote work policy.
Role Overview :
Seeking a high-impact principal data science engineer to join a founding team focused on advancing our mission to combat the skilled worker crisis by unlocking high pay, high dignity careers for talent. The role will have a high degree of autonomy and will have the opportunity to touch all areas of the stack (full stack machine learning, Client operations and API development).
This role represents a chance to join an early-stage team with a focus on creating large-scale positive impact in the world while also generating substantial value in a multi-trillion-dollar industry .
What you'll be doing :
Developing our core technology product, a data-rich system of engagement and record for identifying, qualifying, staffing, optimizing, and retaining skilled talent .
Partnering to build and execute a data strategy in support of the long-term business vision .
Building Client algorithms to support skilled worker retention as well as matching algorithms underlying a labor marketplace.
Flexing across the entire machine learning model development lifecycle, including EDA, data pipelines, feature engineering, model productionisation and monitoring.
nalyzing data (market, user behavior, etc.) to inform new feature development and the associated ROI across our various customer personas .
Ensuring security best-practices around PII and other sensitive data / access .
Bringing values-centered leadership and deep belief in our mission for serving customers, partners, & employees.
Must have :
Tracker record of building and shipping production-grade data products, from 0-1.
Comfortable working across the stack with modern programming languages and frameworks ( Python, Java ) & platforms ( WS, GCP, Azure , etc.).
ble to flex from 100% data science focus to 100% engineering execution based on company needs, with the most likely split being near the center.
Early-stage startup experience.
Nice to have :
Big tech company experience at companies such as : mazon (strongly preferred), pple, Twitter, Amazon, Google, Meta, MicroSoft, Netflix , etc.
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